cryptoPredictor.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOsUFnJDETS2eF6mWThPVyt",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/richod1/cryptoPridiction/blob/main/cryptoPredictor.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "yBfEcrn36VLC"
      },
      "outputs": [],
      "source": [
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
      "metadata": {
        "id": "Q5m_2tOT-qDv"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import yfinance as yf"
      ],
      "metadata": {
        "id": "EHpjn49z-ptQ"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import datetime"
      ],
      "metadata": {
        "id": "hQkHB3X1-pge"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import date,timedelta"
      ],
      "metadata": {
        "id": "Pb8VSvrV-pPk"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "today=date.today()"
      ],
      "metadata": {
        "id": "5BevD0Us-o_1"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "d1=today.strftime(\"%Y-%m-%d\")\n",
        "end_date=d1\n",
        "d2=date.today()-timedelta(days=730)\n",
        "d2=d2.strftime(\"%Y-%m-%d\")\n",
        "start_date=d2"
      ],
      "metadata": {
        "id": "XOZVRPOv-ojJ"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data=yf.download('BTC-USD',start=start_date,progress=False)\n",
        "data[\"Date\"]=data.index\n",
        "data=data[[\"Date\",\"Open\",\"High\",\"Low\",\"Close\",\"Adj Close\",\"Volume\"]]\n",
        "data.reset_index(drop=True,inplace=True)\n",
        "print(data.head(50))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cs_R6prb__Rl",
        "outputId": "aa7d0cf3-57be-465b-ffe1-d0e270d0deef"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "         Date          Open          High           Low         Close  \\\n",
            "0  2022-01-15  43101.898438  43724.671875  42669.035156  43177.398438   \n",
            "1  2022-01-16  43172.039062  43436.808594  42691.023438  43113.878906   \n",
            "2  2022-01-17  43118.121094  43179.390625  41680.320312  42250.550781   \n",
            "3  2022-01-18  42250.074219  42534.402344  41392.214844  42375.632812   \n",
            "4  2022-01-19  42374.039062  42478.304688  41242.914062  41744.328125   \n",
            "5  2022-01-20  41744.027344  43413.023438  40672.824219  40680.417969   \n",
            "6  2022-01-21  40699.605469  41060.527344  35791.425781  36457.316406   \n",
            "7  2022-01-22  36471.589844  36688.812500  34349.250000  35030.250000   \n",
            "8  2022-01-23  35047.359375  36433.312500  34784.968750  36276.804688   \n",
            "9  2022-01-24  36275.734375  37247.519531  33184.058594  36654.328125   \n",
            "10 2022-01-25  36654.804688  37444.570312  35779.429688  36954.003906   \n",
            "11 2022-01-26  36950.515625  38825.410156  36374.906250  36852.121094   \n",
            "12 2022-01-27  36841.878906  37148.324219  35629.281250  37138.234375   \n",
            "13 2022-01-28  37128.445312  37952.878906  36211.109375  37784.332031   \n",
            "14 2022-01-29  37780.714844  38576.261719  37406.472656  38138.179688   \n",
            "15 2022-01-30  38151.917969  38266.339844  37437.710938  37917.601562   \n",
            "16 2022-01-31  37920.281250  38647.261719  36733.574219  38483.125000   \n",
            "17 2022-02-01  38481.765625  39115.132812  38113.664062  38743.273438   \n",
            "18 2022-02-02  38743.714844  38834.617188  36832.730469  36952.984375   \n",
            "19 2022-02-03  36944.804688  37154.601562  36375.539062  37154.601562   \n",
            "20 2022-02-04  37149.265625  41527.785156  37093.628906  41500.875000   \n",
            "21 2022-02-05  41501.480469  41847.164062  41038.097656  41441.164062   \n",
            "22 2022-02-06  41441.121094  42500.785156  41244.906250  42412.433594   \n",
            "23 2022-02-07  42406.781250  44401.863281  41748.156250  43840.285156   \n",
            "24 2022-02-08  43854.652344  45293.867188  42807.835938  44118.445312   \n",
            "25 2022-02-09  44096.703125  44727.800781  43232.968750  44338.796875   \n",
            "26 2022-02-10  44347.800781  45661.171875  43402.808594  43565.113281   \n",
            "27 2022-02-11  43571.128906  43810.832031  42114.539062  42407.937500   \n",
            "28 2022-02-12  42412.300781  42992.550781  41852.574219  42244.468750   \n",
            "29 2022-02-13  42236.566406  42693.054688  41950.941406  42197.515625   \n",
            "30 2022-02-14  42157.398438  42775.777344  41681.957031  42586.917969   \n",
            "31 2022-02-15  42586.464844  44667.218750  42491.035156  44575.203125   \n",
            "32 2022-02-16  44578.277344  44578.277344  43456.691406  43961.859375   \n",
            "33 2022-02-17  43937.070312  44132.972656  40249.371094  40538.011719   \n",
            "34 2022-02-18  40552.132812  40929.152344  39637.617188  40030.976562   \n",
            "35 2022-02-19  40026.023438  40418.878906  39713.058594  40122.156250   \n",
            "36 2022-02-20  40118.101562  40119.890625  38112.812500  38431.378906   \n",
            "37 2022-02-21  38423.210938  39394.437500  36950.476562  37075.281250   \n",
            "38 2022-02-22  37068.769531  38359.855469  36488.933594  38286.027344   \n",
            "39 2022-02-23  38285.281250  39122.394531  37201.816406  37296.570312   \n",
            "40 2022-02-24  37278.566406  38968.839844  34459.218750  38332.609375   \n",
            "41 2022-02-25  38333.746094  39630.324219  38111.343750  39214.218750   \n",
            "42 2022-02-26  39213.082031  40005.347656  38702.535156  39105.148438   \n",
            "43 2022-02-27  39098.699219  39778.941406  37268.976562  37709.785156   \n",
            "44 2022-02-28  37706.000000  43760.457031  37518.214844  43193.234375   \n",
            "45 2022-03-01  43194.503906  44793.601562  42952.585938  44354.636719   \n",
            "46 2022-03-02  44357.617188  45077.578125  43432.851562  43924.117188   \n",
            "47 2022-03-03  43925.195312  44021.578125  41914.750000  42451.789062   \n",
            "48 2022-03-04  42458.140625  42479.613281  38805.847656  39137.605469   \n",
            "49 2022-03-05  39148.449219  39566.335938  38777.035156  39400.585938   \n",
            "\n",
            "       Adj Close       Volume  \n",
            "0   43177.398438  18371348298  \n",
            "1   43113.878906  17902097845  \n",
            "2   42250.550781  21690904261  \n",
            "3   42375.632812  22417209227  \n",
            "4   41744.328125  23091543258  \n",
            "5   40680.417969  20382033940  \n",
            "6   36457.316406  43011992031  \n",
            "7   35030.250000  39714385405  \n",
            "8   36276.804688  26017975951  \n",
            "9   36654.328125  41856658597  \n",
            "10  36954.003906  26428189594  \n",
            "11  36852.121094  31324598034  \n",
            "12  37138.234375  25041426629  \n",
            "13  37784.332031  22238830523  \n",
            "14  38138.179688  17194183075  \n",
            "15  37917.601562  14643548444  \n",
            "16  38483.125000  20734730465  \n",
            "17  38743.273438  20288500328  \n",
            "18  36952.984375  19155189416  \n",
            "19  37154.601562  18591534769  \n",
            "20  41500.875000  29412210792  \n",
            "21  41441.164062  19652846215  \n",
            "22  42412.433594  16142097334  \n",
            "23  43840.285156  28641855926  \n",
            "24  44118.445312  33079398868  \n",
            "25  44338.796875  23245887300  \n",
            "26  43565.113281  32142048537  \n",
            "27  42407.937500  26954925781  \n",
            "28  42244.468750  18152390304  \n",
            "29  42197.515625  14741589015  \n",
            "30  42586.917969  20827783012  \n",
            "31  44575.203125  22721659051  \n",
            "32  43961.859375  19792547657  \n",
            "33  40538.011719  26246662813  \n",
            "34  40030.976562  23310007704  \n",
            "35  40122.156250  13736557863  \n",
            "36  38431.378906  18340576452  \n",
            "37  37075.281250  29280402798  \n",
            "38  38286.027344  25493150450  \n",
            "39  37296.570312  21849073843  \n",
            "40  38332.609375  46383802093  \n",
            "41  39214.218750  26545599159  \n",
            "42  39105.148438  17467554129  \n",
            "43  37709.785156  23450127612  \n",
            "44  43193.234375  35690014104  \n",
            "45  44354.636719  32479047645  \n",
            "46  43924.117188  29183112630  \n",
            "47  42451.789062  24967782593  \n",
            "48  39137.605469  28516271427  \n",
            "49  39400.585938  16975917450  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0yOkAS4i_-fs",
        "outputId": "1008b63a-97fa-4441-f22e-88468c832b6a"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(731, 7)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import plotly.graph_objects as go\n",
        "figure=go.Figure(data=[go.Candlestick(x=data[\"Date\"],open=data[\"Open\"],high=data[\"High\"],low=data[\"Low\"],close=data[\"Close\"])])\n",
        "figure.update_layout(title=\"Bitcoin Price Analysis\",xaxis_rangeslider_visible=False)\n",
        "figure.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "CIO0CutN_96N",
        "outputId": "798e0798-fd07-44ca-e2dd-18e8e90cfe9d"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
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          "metadata": {}
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "correlation=data.corr()\n",
        "print(correlation[\"Close\"].sort_values(ascending=False))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "59a9CYglEwfy",
        "outputId": "70db77e8-1ab6-4b47-bfe5-e6911eee9203"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Close        1.000000\n",
            "Adj Close    1.000000\n",
            "High         0.997580\n",
            "Low          0.997506\n",
            "Open         0.994606\n",
            "Volume      -0.069004\n",
            "Name: Close, dtype: float64\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-16-61c131bd6a99>:1: FutureWarning:\n",
            "\n",
            "The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install autots"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2yghM7otEwJK",
        "outputId": "31b3a292-27c2-4b2f-c3ab-b9229ed765ce"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting autots\n",
            "  Downloading autots-0.6.7-py3-none-any.whl (821 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m821.5/821.5 kB\u001b[0m \u001b[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.14.6 in /usr/local/lib/python3.10/dist-packages (from autots) (1.23.5)\n",
            "Requirement already satisfied: pandas>=0.25.0 in /usr/local/lib/python3.10/dist-packages (from autots) (1.5.3)\n",
            "Requirement already satisfied: statsmodels>=0.10.0 in /usr/local/lib/python3.10/dist-packages (from autots) (0.14.1)\n",
            "Requirement already satisfied: scikit-learn>=0.20.0 in /usr/local/lib/python3.10/dist-packages (from autots) (1.2.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=0.25.0->autots) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=0.25.0->autots) (2023.3.post1)\n",
            "Requirement already satisfied: scipy>=1.3.2 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.20.0->autots) (1.11.4)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.20.0->autots) (1.3.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.20.0->autots) (3.2.0)\n",
            "Requirement already satisfied: patsy>=0.5.4 in /usr/local/lib/python3.10/dist-packages (from statsmodels>=0.10.0->autots) (0.5.6)\n",
            "Requirement already satisfied: packaging>=21.3 in /usr/local/lib/python3.10/dist-packages (from statsmodels>=0.10.0->autots) (23.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from patsy>=0.5.4->statsmodels>=0.10.0->autots) (1.16.0)\n",
            "Installing collected packages: autots\n",
            "Successfully installed autots-0.6.7\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from autots import AutoTS\n",
        "model=AutoTS(forecast_length=30,frequency='infer',ensemble='simple')\n",
        "model=model.fit(data,date_col='Date',value_col='Close',id_col=None)\n",
        "prediction=model.predict()\n",
        "forecast=prediction.forecast\n",
        "print(forecast)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w2CuQqHgEvyT",
        "outputId": "ab2bb396-47ff-4739-c360-fd342ce20f76"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data frequency is: D, used frequency is: D\n",
            "Model Number: 1 with model ARIMA in generation 0 of 10\n",
            "Model Number: 2 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 3 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 4 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 5 with model DatepartRegression in generation 0 of 10\n",
            "Model Number: 6 with model DatepartRegression in generation 0 of 10\n",
            "Model Number: 7 with model DatepartRegression in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:541: ConvergenceWarning:\n",
            "\n",
            "lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 8 with model DatepartRegression in generation 0 of 10\n",
            "Epoch 1/50\n",
            "22/22 [==============================] - 7s 8ms/step - loss: 0.4141\n",
            "Epoch 2/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.4057\n",
            "Epoch 3/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.3932\n",
            "Epoch 4/50\n",
            "22/22 [==============================] - 0s 11ms/step - loss: 0.3793\n",
            "Epoch 5/50\n",
            "22/22 [==============================] - 0s 11ms/step - loss: 0.3660\n",
            "Epoch 6/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3654\n",
            "Epoch 7/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.3611\n",
            "Epoch 8/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3584\n",
            "Epoch 9/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.3594\n",
            "Epoch 10/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3559\n",
            "Epoch 11/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3526\n",
            "Epoch 12/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3578\n",
            "Epoch 13/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.3650\n",
            "Epoch 14/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3553\n",
            "Epoch 15/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3502\n",
            "Epoch 16/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3495\n",
            "Epoch 17/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3499\n",
            "Epoch 18/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.3464\n",
            "Epoch 19/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.3440\n",
            "Epoch 20/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3481\n",
            "Epoch 21/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3516\n",
            "Epoch 22/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3438\n",
            "Epoch 23/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3470\n",
            "Epoch 24/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3422\n",
            "Epoch 25/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3452\n",
            "Epoch 26/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3486\n",
            "Epoch 27/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3479\n",
            "Epoch 28/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3440\n",
            "Epoch 29/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3390\n",
            "Epoch 30/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3397\n",
            "Epoch 31/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3410\n",
            "Epoch 32/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3407\n",
            "Epoch 33/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3434\n",
            "Epoch 34/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3441\n",
            "Epoch 35/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3420\n",
            "Epoch 36/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.3388\n",
            "Epoch 37/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3369\n",
            "Epoch 38/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3354\n",
            "Epoch 39/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3401\n",
            "Epoch 40/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3344\n",
            "Epoch 41/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3393\n",
            "Epoch 42/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.3383\n",
            "Epoch 43/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3368\n",
            "Epoch 44/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3335\n",
            "Epoch 45/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3336\n",
            "Epoch 46/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3329\n",
            "Epoch 47/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3341\n",
            "Epoch 48/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3350\n",
            "Epoch 49/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.3344\n",
            "Epoch 50/50\n",
            "22/22 [==============================] - 0s 6ms/step - loss: 0.3314\n",
            "1/1 [==============================] - 1s 1s/step\n",
            "Model Number: 9 with model ETS in generation 0 of 10\n",
            "Model Number: 10 with model ETS in generation 0 of 10\n",
            "Model Number: 11 with model GLM in generation 0 of 10\n",
            "Model Number: 12 with model GLM in generation 0 of 10\n",
            "Model Number: 13 with model GLS in generation 0 of 10\n",
            "Model Number: 14 with model GLS in generation 0 of 10\n",
            "Model Number: 15 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 15 in generation 0: GluonTS\n",
            "Model Number: 16 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 16 in generation 0: GluonTS\n",
            "Model Number: 17 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 17 in generation 0: GluonTS\n",
            "Model Number: 18 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 18 in generation 0: GluonTS\n",
            "Model Number: 19 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 19 in generation 0: GluonTS\n",
            "Model Number: 20 with model LastValueNaive in generation 0 of 10\n",
            "Model Number: 21 with model LastValueNaive in generation 0 of 10\n",
            "Model Number: 22 with model LastValueNaive in generation 0 of 10\n",
            "Model Number: 23 with model LastValueNaive in generation 0 of 10\n",
            "Model Number: 24 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 25 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 26 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 27 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 28 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 29 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 30 with model VAR in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VAR') in model 30 in generation 0: VAR\n",
            "Model Number: 31 with model VAR in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VAR') in model 31 in generation 0: VAR\n",
            "Model Number: 32 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 32 in generation 0: VECM\n",
            "Model Number: 33 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 33 in generation 0: VECM\n",
            "Model Number: 34 with model WindowRegression in generation 0 of 10\n",
            "Model Number: 35 with model ConstantNaive in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:541: ConvergenceWarning:\n",
            "\n",
            "lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 36 with model FBProphet in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:cmdstanpy:input tempfile: /tmp/tmpd95gco7h/ksf_pknk.json\n",
            "DEBUG:cmdstanpy:input tempfile: /tmp/tmpd95gco7h/lq0w8wzt.json\n",
            "DEBUG:cmdstanpy:idx 0\n",
            "DEBUG:cmdstanpy:running CmdStan, num_threads: None\n",
            "DEBUG:cmdstanpy:CmdStan args: ['/usr/local/lib/python3.10/dist-packages/prophet/stan_model/prophet_model.bin', 'random', 'seed=34797', 'data', 'file=/tmp/tmpd95gco7h/ksf_pknk.json', 'init=/tmp/tmpd95gco7h/lq0w8wzt.json', 'output', 'file=/tmp/tmpd95gco7h/prophet_model12lcc47z/prophet_model-20240115215653.csv', 'method=optimize', 'algorithm=lbfgs', 'iter=10000']\n",
            "21:56:53 - cmdstanpy - INFO - Chain [1] start processing\n",
            "INFO:cmdstanpy:Chain [1] start processing\n",
            "21:56:54 - cmdstanpy - INFO - Chain [1] done processing\n",
            "INFO:cmdstanpy:Chain [1] done processing\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 37 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 37 in generation 0: GluonTS\n",
            "Model Number: 38 with model MultivariateRegression in generation 0 of 10\n",
            "Model Number: 39 with model MultivariateRegression in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 39 in generation 0: MultivariateRegression\n",
            "Model Number: 40 with model DatepartRegression in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 40 in generation 0: DatepartRegression\n",
            "Model Number: 41 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 42 with model DatepartRegression in generation 0 of 10\n",
            "Model Number: 43 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 44 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 45 with model ETS in generation 0 of 10\n",
            "Model Number: 46 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 46 in generation 0: VECM\n",
            "Model Number: 47 with model ARDL in generation 0 of 10\n",
            "Model Number: 48 with model MultivariateMotif in generation 0 of 10\n",
            "Model Number: 49 with model MultivariateMotif in generation 0 of 10\n",
            "Model Number: 50 with model UnivariateMotif in generation 0 of 10\n",
            "Model Number: 51 with model UnivariateMotif in generation 0 of 10\n",
            "Model Number: 52 with model SectionalMotif in generation 0 of 10\n",
            "Model Number: 53 with model SectionalMotif in generation 0 of 10\n",
            "Model Number: 54 with model MultivariateRegression in generation 0 of 10\n",
            "Model Number: 55 with model FBProphet in generation 0 of 10\n",
            "Model Number: 56 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 57 with model DatepartRegression in generation 0 of 10\n",
            "Model Number: 58 with model NVAR in generation 0 of 10\n",
            "Model Number: 59 with model Theta in generation 0 of 10\n",
            "Model Number: 60 with model UnivariateRegression in generation 0 of 10\n",
            "Model Number: 61 with model ARCH in generation 0 of 10\n",
            "Template Eval Error: ImportError('`arch` package must be installed from pip') in model 61 in generation 0: ARCH\n",
            "Model Number: 62 with model ConstantNaive in generation 0 of 10\n",
            "Model Number: 63 with model LastValueNaive in generation 0 of 10\n",
            "Model Number: 64 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 65 with model GLS in generation 0 of 10\n",
            "Model Number: 66 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 67 with model GLM in generation 0 of 10\n",
            "Model Number: 68 with model ETS in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:198: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 69 with model FBProphet in generation 0 of 10\n",
            "Model Number: 70 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 70 in generation 0: GluonTS\n",
            "Model Number: 71 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 72 with model VAR in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VAR') in model 72 in generation 0: VAR\n",
            "Model Number: 73 with model VECM in generation 0 of 10\n",
            "Template Eval Error: LinAlgError('Singular matrix') in model 73 in generation 0: VECM\n",
            "Model Number: 74 with model ARIMA in generation 0 of 10\n",
            "Model Number: 75 with model WindowRegression in generation 0 of 10\n",
            "Model Number: 76 with model DatepartRegression in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 76 in generation 0: DatepartRegression\n",
            "Model Number: 77 with model UnivariateRegression in generation 0 of 10\n",
            "Model Number: 78 with model MultivariateRegression in generation 0 of 10\n",
            "Model Number: 79 with model UnivariateMotif in generation 0 of 10\n",
            "Model Number: 80 with model MultivariateMotif in generation 0 of 10\n",
            "Model Number: 81 with model SectionalMotif in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 81 in generation 0: SectionalMotif\n",
            "Model Number: 82 with model NVAR in generation 0 of 10\n",
            "Model Number: 83 with model Theta in generation 0 of 10\n",
            "Model Number: 84 with model ARDL in generation 0 of 10\n",
            "Model Number: 85 with model ARCH in generation 0 of 10\n",
            "Template Eval Error: ImportError('`arch` package must be installed from pip') in model 85 in generation 0: ARCH\n",
            "Model Number: 86 with model MetricMotif in generation 0 of 10\n",
            "Model Number: 87 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 87 in generation 0: GluonTS\n",
            "Model Number: 88 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 89 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 90 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 91 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 92 with model SectionalMotif in generation 0 of 10\n",
            "Template Eval Error: ValueError('Unknown Distance Metric: kulsinski') in model 92 in generation 0: SectionalMotif\n",
            "Model Number: 93 with model ARIMA in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but future_regressor not supplied\") in model 93 in generation 0: ARIMA\n",
            "Model Number: 94 with model Theta in generation 0 of 10\n",
            "Model Number: 95 with model ARDL in generation 0 of 10\n",
            "Model Number: 96 with model VAR in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"x contains one or more constant columns. Column(s) 1 are constant. Adding a constant with trend='c' is not allowed.\") in model 96 in generation 0: VAR\n",
            "Model Number: 97 with model UnivariateMotif in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 97 in generation 0: UnivariateMotif\n",
            "Model Number: 98 with model MultivariateMotif in generation 0 of 10\n",
            "Model Number: 99 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 100 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 100 in generation 0: GluonTS\n",
            "Model Number: 101 with model ConstantNaive in generation 0 of 10\n",
            "Model Number: 102 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 103 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 104 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 104 in generation 0: VECM\n",
            "Model Number: 105 with model ETS in generation 0 of 10\n",
            "Model Number: 106 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 107 with model LastValueNaive in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning:\n",
            "\n",
            "Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.292e+08, tolerance: 3.265e+05\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 108 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 108 in generation 0: VECM\n",
            "Model Number: 109 with model SectionalMotif in generation 0 of 10\n",
            "Template Eval Error: ValueError('kth(=20) out of bounds (13)') in model 109 in generation 0: SectionalMotif\n",
            "Model Number: 110 with model DatepartRegression in generation 0 of 10\n",
            "Model Number: 111 with model SectionalMotif in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type=='User' but no future_regressor supplied\") in model 111 in generation 0: SectionalMotif\n",
            "Model Number: 112 with model MetricMotif in generation 0 of 10\n",
            "Model Number: 113 with model Theta in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 113 in generation 0: Theta\n",
            "Model Number: 114 with model SectionalMotif in generation 0 of 10\n",
            "Model Number: 115 with model NVAR in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 115 in generation 0: NVAR\n",
            "Model Number: 116 with model LastValueNaive in generation 0 of 10\n",
            "Model Number: 117 with model GLS in generation 0 of 10\n",
            "Model Number: 118 with model SeasonalNaive in generation 0 of 10\n",
            "Model Number: 119 with model GLM in generation 0 of 10\n",
            "Model Number: 120 with model GluonTS in generation 0 of 10\n",
            "Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 120 in generation 0: GluonTS\n",
            "Model Number: 121 with model ETS in generation 0 of 10\n",
            "Model Number: 122 with model NVAR in generation 0 of 10\n",
            "Model Number: 123 with model ARDL in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 123 in generation 0: ARDL\n",
            "Model Number: 124 with model GLM in generation 0 of 10\n",
            "Template Eval Error: ValueError('NaN, inf or invalid value detected in weights, estimation infeasible.') in model 124 in generation 0: GLM\n",
            "Model Number: 125 with model DatepartRegression in generation 0 of 10\n",
            "Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 125 in generation 0: DatepartRegression\n",
            "Model Number: 126 with model LastValueNaive in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:445: RuntimeWarning:\n",
            "\n",
            "divide by zero encountered in divide\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:143: RuntimeWarning:\n",
            "\n",
            "divide by zero encountered in divide\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_regression.py:494: UserWarning:\n",
            "\n",
            "One or more samples have no neighbors within specified radius; predicting NaN.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 127 with model NVAR in generation 0 of 10\n",
            "Model Number: 128 with model WindowRegression in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 128 in generation 0: WindowRegression\n",
            "Model Number: 129 with model MultivariateMotif in generation 0 of 10\n",
            "Model Number: 130 with model Theta in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 130 in generation 0: Theta\n",
            "Model Number: 131 with model MetricMotif in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer HolidayTransformer failed on fit') in model 131 in generation 0: MetricMotif\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_ridge.py:216: LinAlgWarning:\n",
            "\n",
            "Ill-conditioned matrix (rcond=1.52185e-25): result may not be accurate.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 132 with model UnobservedComponents in generation 0 of 10\n",
            "Model Number: 133 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 134 with model SectionalMotif in generation 0 of 10\n",
            "Template Eval Error: ValueError('Unknown Distance Metric: kulsinski') in model 134 in generation 0: SectionalMotif\n",
            "Model Number: 135 with model LastValueNaive in generation 0 of 10\n",
            "Model Number: 136 with model FBProphet in generation 0 of 10\n",
            "Model Number: 137 with model Theta in generation 0 of 10\n",
            "Model Number: 138 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 139 with model UnivariateMotif in generation 0 of 10\n",
            "Model Number: 140 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 141 with model MultivariateMotif in generation 0 of 10\n",
            "Template Eval Error: IndexError('index 310 is out of bounds for axis 0 with size 1') in model 141 in generation 0: MultivariateMotif\n",
            "Model Number: 142 with model DatepartRegression in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_ridge.py:216: LinAlgWarning:\n",
            "\n",
            "Ill-conditioned matrix (rcond=1.52185e-25): result may not be accurate.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 143 with model UnivariateMotif in generation 0 of 10\n",
            "Model Number: 144 with model ARIMA in generation 0 of 10\n",
            "Model Number: 145 with model MetricMotif in generation 0 of 10\n",
            "Model Number: 146 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 146 in generation 0: VECM\n",
            "Model Number: 147 with model ETS in generation 0 of 10\n",
            "Model Number: 148 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 148 in generation 0: VECM\n",
            "Model Number: 149 with model ConstantNaive in generation 0 of 10\n",
            "Model Number: 150 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VECM') in model 150 in generation 0: VECM\n",
            "Model Number: 151 with model Theta in generation 0 of 10\n",
            "Model Number: 152 with model UnobservedComponents in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer HolidayTransformer failed on fit') in model 152 in generation 0: UnobservedComponents\n",
            "Model Number: 153 with model NVAR in generation 0 of 10\n",
            "Model Number: 154 with model NVAR in generation 0 of 10\n",
            "Model Number: 155 with model GLS in generation 0 of 10\n",
            "Model Number: 156 with model GLM in generation 0 of 10\n",
            "Template Eval Error: ValueError('Model GLM returned NaN for one or more series. fail_on_forecast_nan=True') in model 156 in generation 0: GLM\n",
            "Model Number: 157 with model GLS in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1402: RuntimeWarning:\n",
            "\n",
            "divide by zero encountered in divide\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:527: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1406: RuntimeWarning:\n",
            "\n",
            "divide by zero encountered in log\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 158 with model GLM in generation 0 of 10\n",
            "Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 158 in generation 0: GLM\n",
            "Model Number: 159 with model ETS in generation 0 of 10\n",
            "Model Number: 160 with model GLS in generation 0 of 10\n",
            "Model Number: 161 with model SectionalMotif in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type=='User' but no future_regressor supplied\") in model 161 in generation 0: SectionalMotif\n",
            "Model Number: 162 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 163 with model VAR in generation 0 of 10\n",
            "Template Eval Error: ValueError('Only gave one variable to VAR') in model 163 in generation 0: VAR\n",
            "Model Number: 164 with model DatepartRegression in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 164 in generation 0: DatepartRegression\n",
            "Model Number: 165 with model WindowRegression in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 165 in generation 0: WindowRegression\n",
            "Model Number: 166 with model GLS in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 166 in generation 0: GLS\n",
            "Model Number: 167 with model VECM in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 167 in generation 0: VECM\n",
            "Model Number: 168 with model AverageValueNaive in generation 0 of 10\n",
            "Model Number: 169 with model MultivariateMotif in generation 0 of 10\n",
            "Template Eval Error: Exception('Transformer HolidayTransformer failed on fit') in model 169 in generation 0: MultivariateMotif\n",
            "Model Number: 170 with model UnivariateMotif in generation 0 of 10\n",
            "Model Number: 171 with model ARDL in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but future_regressor not supplied\") in model 171 in generation 0: ARDL\n",
            "Model Number: 172 with model MultivariateMotif in generation 0 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_ridge.py:216: LinAlgWarning:\n",
            "\n",
            "Ill-conditioned matrix (rcond=1.52185e-25): result may not be accurate.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 173 with model VECM in generation 0 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor supplied\") in model 173 in generation 0: VECM\n",
            "Model Number: 174 with model ETS in generation 0 of 10\n",
            "Model Number: 175 with model Theta in generation 0 of 10\n",
            "Model Number: 176 with model NVAR in generation 0 of 10\n",
            "Model Number: 177 with model GLM in generation 0 of 10\n",
            "Model Number: 178 with model ARCH in generation 0 of 10\n",
            "Template Eval Error: ImportError('`arch` package must be installed from pip') in model 178 in generation 0: ARCH\n",
            "Model Number: 179 with model ARCH in generation 0 of 10\n",
            "Template Eval Error: ImportError('`arch` package must be installed from pip') in model 179 in generation 0: ARCH\n",
            "Model Number: 180 with model GLS in generation 0 of 10\n",
            "Model Number: 181 with model ConstantNaive in generation 0 of 10\n",
            "Model Number: 182 with model ETS in generation 0 of 10\n",
            "Model Number: 183 with model UnivariateMotif in generation 0 of 10\n",
            "Model Number: 184 with model ETS in generation 0 of 10\n",
            "Model Number: 185 with model ARCH in generation 0 of 10\n",
            "Template Eval Error: ImportError('`arch` package must be installed from pip') in model 185 in generation 0: ARCH\n",
            "Model Number: 186 with model AverageValueNaive in generation 0 of 10\n",
            "New Generation: 1 of 10\n",
            "Model Number: 187 with model ARIMA in generation 1 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 187 in generation 1: ARIMA\n",
            "Model Number: 188 with model Theta in generation 1 of 10\n",
            "Model Number: 189 with model DatepartRegression in generation 1 of 10\n",
            "Model Number: 190 with model GLM in generation 1 of 10\n",
            "Model Number: 191 with model WindowRegression in generation 1 of 10\n",
            "Model Number: 192 with model ConstantNaive in generation 1 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 192 in generation 1: ConstantNaive\n",
            "Model Number: 193 with model MultivariateRegression in generation 1 of 10\n",
            "Template Eval Error: ValueError('Some value(s) of y are negative which is not allowed for Poisson regression.') in model 193 in generation 1: MultivariateRegression\n",
            "Model Number: 194 with model ETS in generation 1 of 10\n",
            "Model Number: 195 with model NVAR in generation 1 of 10\n",
            "Model Number: 196 with model UnobservedComponents in generation 1 of 10\n",
            "Model Number: 197 with model SeasonalNaive in generation 1 of 10\n",
            "Model Number: 198 with model ARDL in generation 1 of 10\n",
            "Model Number: 199 with model ConstantNaive in generation 1 of 10\n",
            "Model Number: 200 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 201 with model GLS in generation 1 of 10\n",
            "Model Number: 202 with model ConstantNaive in generation 1 of 10\n",
            "Model Number: 203 with model SeasonalNaive in generation 1 of 10\n",
            "Model Number: 204 with model Theta in generation 1 of 10\n",
            "Model Number: 205 with model FBProphet in generation 1 of 10\n",
            "Model Number: 206 with model ConstantNaive in generation 1 of 10\n",
            "Model Number: 207 with model UnivariateMotif in generation 1 of 10\n",
            "Model Number: 208 with model NVAR in generation 1 of 10\n",
            "Model Number: 209 with model ARDL in generation 1 of 10\n",
            "Template Eval Error: ValueError(\"ARDL series Close failed with error IndexError('tuple index out of range') exog train None and predict None\") in model 209 in generation 1: ARDL\n",
            "Model Number: 210 with model MultivariateMotif in generation 1 of 10\n",
            "Model Number: 211 with model ARIMA in generation 1 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 211 in generation 1: ARIMA\n",
            "Model Number: 212 with model ConstantNaive in generation 1 of 10\n",
            "Model Number: 213 with model ARIMA in generation 1 of 10\n",
            "Model Number: 214 with model SeasonalNaive in generation 1 of 10\n",
            "Model Number: 215 with model NVAR in generation 1 of 10\n",
            "Model Number: 216 with model UnivariateMotif in generation 1 of 10\n",
            "Model Number: 217 with model AverageValueNaive in generation 1 of 10\n",
            "Template Eval Error: Exception('Transformer StandardScaler failed on inverse') in model 217 in generation 1: AverageValueNaive\n",
            "Model Number: 218 with model MultivariateRegression in generation 1 of 10\n",
            "Model Number: 219 with model FBProphet in generation 1 of 10\n",
            "Model Number: 220 with model UnivariateMotif in generation 1 of 10\n",
            "Model Number: 221 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 222 with model Theta in generation 1 of 10\n",
            "Model Number: 223 with model WindowRegression in generation 1 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 223 in generation 1: WindowRegression\n",
            "Model Number: 224 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 225 with model GLM in generation 1 of 10\n",
            "Model Number: 226 with model DatepartRegression in generation 1 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_regression.py:494: UserWarning:\n",
            "\n",
            "One or more samples have no neighbors within specified radius; predicting NaN.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 226 in generation 1: DatepartRegression\n",
            "Model Number: 227 with model UnivariateRegression in generation 1 of 10\n",
            "Model Number: 228 with model ETS in generation 1 of 10\n",
            "Model Number: 229 with model ETS in generation 1 of 10\n",
            "Model Number: 230 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 231 with model GLS in generation 1 of 10\n",
            "Model Number: 232 with model UnivariateMotif in generation 1 of 10\n",
            "Model Number: 233 with model SectionalMotif in generation 1 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 233 in generation 1: SectionalMotif\n",
            "Model Number: 234 with model NVAR in generation 1 of 10\n",
            "Model Number: 235 with model DatepartRegression in generation 1 of 10\n",
            "Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 235 in generation 1: DatepartRegression\n",
            "Model Number: 236 with model AverageValueNaive in generation 1 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_regression.py:494: UserWarning:\n",
            "\n",
            "One or more samples have no neighbors within specified radius; predicting NaN.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 237 with model Theta in generation 1 of 10\n",
            "Model Number: 238 with model UnobservedComponents in generation 1 of 10\n",
            "Model Number: 239 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 240 with model FBProphet in generation 1 of 10\n",
            "Model Number: 241 with model LastValueNaive in generation 1 of 10\n",
            "Template Eval Error: Exception('Transformer PowerTransformer failed on fit') in model 241 in generation 1: LastValueNaive\n",
            "Model Number: 242 with model NVAR in generation 1 of 10\n",
            "Model Number: 243 with model AverageValueNaive in generation 1 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/preprocessing/_data.py:3256: RuntimeWarning:\n",
            "\n",
            "overflow encountered in power\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 244 with model Theta in generation 1 of 10\n",
            "Model Number: 245 with model MultivariateRegression in generation 1 of 10\n",
            "Model Number: 246 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 247 with model SeasonalNaive in generation 1 of 10\n",
            "Model Number: 248 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 249 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 250 with model DatepartRegression in generation 1 of 10\n",
            "Model Number: 251 with model NVAR in generation 1 of 10\n",
            "Model Number: 252 with model Theta in generation 1 of 10\n",
            "Model Number: 253 with model Theta in generation 1 of 10\n",
            "Model Number: 254 with model ETS in generation 1 of 10\n",
            "Model Number: 255 with model ETS in generation 1 of 10\n",
            "Model Number: 256 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 257 with model ARDL in generation 1 of 10\n",
            "Model Number: 258 with model MultivariateRegression in generation 1 of 10\n",
            "Template Eval Error: XGBoostError('[21:57:53] /workspace/src/objective/regression_obj.cu:530: GammaRegression: label must be positive.\\nStack trace:\\n  [bt] (0) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0xa8dc0a) [0x794513eafc0a]\\n  [bt] (1) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0xaa1ac7) [0x794513ec3ac7]\\n  [bt] (2) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x55f9ed) [0x7945139819ed]\\n  [bt] (3) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x4900d1) [0x7945138b20d1]\\n  [bt] (4) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x4c0716) [0x7945138e2716]\\n  [bt] (5) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x4c5274) [0x7945138e7274]\\n  [bt] (6) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(XGBoosterUpdateOneIter+0x70) [0x794513583ef0]\\n  [bt] (7) /lib/x86_64-linux-gnu/libffi.so.8(+0x7e2e) [0x7945f242ce2e]\\n  [bt] (8) /lib/x86_64-linux-gnu/libffi.so.8(+0x4493) [0x7945f2429493]\\n\\n') in model 258 in generation 1: MultivariateRegression\n",
            "Model Number: 259 with model ConstantNaive in generation 1 of 10\n",
            "Model Number: 260 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 261 with model SeasonalNaive in generation 1 of 10\n",
            "Model Number: 262 with model ConstantNaive in generation 1 of 10\n",
            "Model Number: 263 with model SeasonalNaive in generation 1 of 10\n",
            "Model Number: 264 with model GLM in generation 1 of 10\n",
            "Model Number: 265 with model DatepartRegression in generation 1 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 266 with model DatepartRegression in generation 1 of 10\n",
            "Model Number: 267 with model UnobservedComponents in generation 1 of 10\n",
            "Model Number: 268 with model UnobservedComponents in generation 1 of 10\n",
            "Model Number: 269 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 270 with model ETS in generation 1 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 270 in generation 1: ETS\n",
            "Model Number: 271 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 272 with model GLS in generation 1 of 10\n",
            "Model Number: 273 with model ETS in generation 1 of 10\n",
            "Model Number: 274 with model FBProphet in generation 1 of 10\n",
            "Model Number: 275 with model GLM in generation 1 of 10\n",
            "Model Number: 276 with model NVAR in generation 1 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 277 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 278 with model UnivariateMotif in generation 1 of 10\n",
            "Model Number: 279 with model MultivariateMotif in generation 1 of 10\n",
            "Model Number: 280 with model Theta in generation 1 of 10\n",
            "Model Number: 281 with model ARDL in generation 1 of 10\n",
            "Model Number: 282 with model ARIMA in generation 1 of 10\n",
            "Model Number: 283 with model ETS in generation 1 of 10\n",
            "Model Number: 284 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 285 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 286 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 287 with model UnivariateMotif in generation 1 of 10\n",
            "Model Number: 288 with model WindowRegression in generation 1 of 10\n",
            "Model Number: 289 with model GLM in generation 1 of 10\n",
            "Model Number: 290 with model GLS in generation 1 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 291 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 292 with model LastValueNaive in generation 1 of 10\n",
            "Model Number: 293 with model Theta in generation 1 of 10\n",
            "Model Number: 294 with model MultivariateMotif in generation 1 of 10\n",
            "Model Number: 295 with model UnobservedComponents in generation 1 of 10\n",
            "Model Number: 296 with model UnobservedComponents in generation 1 of 10\n",
            "Model Number: 297 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 298 with model MultivariateRegression in generation 1 of 10\n",
            "Model Number: 299 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 300 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 301 with model NVAR in generation 1 of 10\n",
            "Model Number: 302 with model UnobservedComponents in generation 1 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 303 with model Theta in generation 1 of 10\n",
            "Model Number: 304 with model UnivariateMotif in generation 1 of 10\n",
            "Model Number: 305 with model MetricMotif in generation 1 of 10\n",
            "Model Number: 306 with model DatepartRegression in generation 1 of 10\n",
            "Epoch 1/50\n",
            "22/22 [==============================] - 7s 9ms/step - loss: 0.0415\n",
            "Epoch 2/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 0.0418\n",
            "Epoch 3/50\n",
            "22/22 [==============================] - 0s 15ms/step - loss: 0.0409\n",
            "Epoch 4/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 0.0412\n",
            "Epoch 5/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 0.0408\n",
            "Epoch 6/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 0.0407\n",
            "Epoch 7/50\n",
            "22/22 [==============================] - 0s 14ms/step - loss: 0.0404\n",
            "Epoch 8/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 0.0403\n",
            "Epoch 9/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.0402\n",
            "Epoch 10/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.0407\n",
            "Epoch 11/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.0402\n",
            "Epoch 12/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.0404\n",
            "Epoch 13/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.0400\n",
            "Epoch 14/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.0400\n",
            "Epoch 15/50\n",
            "22/22 [==============================] - 0s 11ms/step - loss: 0.0399\n",
            "Epoch 16/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 0.0400\n",
            "Epoch 17/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.0402\n",
            "Epoch 18/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0399\n",
            "Epoch 19/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0396\n",
            "Epoch 20/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0390\n",
            "Epoch 21/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0393\n",
            "Epoch 22/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0394\n",
            "Epoch 23/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0397\n",
            "Epoch 24/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0392\n",
            "Epoch 25/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0393\n",
            "Epoch 26/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0395\n",
            "Epoch 27/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0390\n",
            "Epoch 28/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0390\n",
            "Epoch 29/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0387\n",
            "Epoch 30/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0389\n",
            "Epoch 31/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0391\n",
            "Epoch 32/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0390\n",
            "Epoch 33/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0386\n",
            "Epoch 34/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0391\n",
            "Epoch 35/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0386\n",
            "Epoch 36/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0382\n",
            "Epoch 37/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0379\n",
            "Epoch 38/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0372\n",
            "Epoch 39/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0387\n",
            "Epoch 40/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0389\n",
            "Epoch 41/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.0382\n",
            "Epoch 42/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.0384\n",
            "Epoch 43/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.0377\n",
            "Epoch 44/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 0.0377\n",
            "Epoch 45/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0377\n",
            "Epoch 46/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0376\n",
            "Epoch 47/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0375\n",
            "Epoch 48/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0366\n",
            "Epoch 49/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 0.0366\n",
            "Epoch 50/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 0.0372\n",
            "1/1 [==============================] - 1s 1s/step\n",
            "Model Number: 307 with model ETS in generation 1 of 10\n",
            "Model Number: 308 with model ARIMA in generation 1 of 10\n",
            "Model Number: 309 with model MetricMotif in generation 1 of 10\n",
            "Model Number: 310 with model AverageValueNaive in generation 1 of 10\n",
            "Model Number: 311 with model MetricMotif in generation 1 of 10\n",
            "New Generation: 2 of 10\n",
            "Model Number: 312 with model GLS in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 313 with model LastValueNaive in generation 2 of 10\n",
            "Model Number: 314 with model ARIMA in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer Detrend failed on fit') in model 314 in generation 2: ARIMA\n",
            "Model Number: 315 with model ARIMA in generation 2 of 10\n",
            "Model Number: 316 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 317 with model ARDL in generation 2 of 10\n",
            "Model Number: 318 with model LastValueNaive in generation 2 of 10\n",
            "Model Number: 319 with model NVAR in generation 2 of 10\n",
            "Model Number: 320 with model MetricMotif in generation 2 of 10\n",
            "Model Number: 321 with model NVAR in generation 2 of 10\n",
            "Template Eval Error: ValueError('Model NVAR returned NaN for one or more series. fail_on_forecast_nan=True') in model 321 in generation 2: NVAR\n",
            "Model Number: 322 with model ConstantNaive in generation 2 of 10\n",
            "Model Number: 323 with model DatepartRegression in generation 2 of 10\n",
            "Model Number: 324 with model ARIMA in generation 2 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but future_regressor not supplied\") in model 324 in generation 2: ARIMA\n",
            "Model Number: 325 with model LastValueNaive in generation 2 of 10\n",
            "Model Number: 326 with model UnivariateMotif in generation 2 of 10\n",
            "Model Number: 327 with model LastValueNaive in generation 2 of 10\n",
            "Model Number: 328 with model GLS in generation 2 of 10\n",
            "Model Number: 329 with model DatepartRegression in generation 2 of 10\n",
            "Model Number: 330 with model GLS in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/autots/tools/fast_kalman.py:1306: RuntimeWarning:\n",
            "\n",
            "invalid value encountered in matmul\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Template Eval Error: ValueError('zero-size array to reduction operation maximum which has no identity') in model 330 in generation 2: GLS\n",
            "Model Number: 331 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 332 with model Theta in generation 2 of 10\n",
            "Model Number: 333 with model AverageValueNaive in generation 2 of 10\n",
            "Model Number: 334 with model SectionalMotif in generation 2 of 10\n",
            "Template Eval Error: ValueError('kth(=15) out of bounds (13)') in model 334 in generation 2: SectionalMotif\n",
            "Model Number: 335 with model WindowRegression in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/experimental/enable_hist_gradient_boosting.py:16: UserWarning:\n",
            "\n",
            "Since version 1.0, it is not needed to import enable_hist_gradient_boosting anymore. HistGradientBoostingClassifier and HistGradientBoostingRegressor are now stable and can be normally imported from sklearn.ensemble.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 336 with model AverageValueNaive in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 336 in generation 2: AverageValueNaive\n",
            "Model Number: 337 with model UnivariateRegression in generation 2 of 10\n",
            "Model Number: 338 with model GLS in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 339 with model MultivariateMotif in generation 2 of 10\n",
            "Model Number: 340 with model ARIMA in generation 2 of 10\n",
            "Model Number: 341 with model LastValueNaive in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 341 in generation 2: LastValueNaive\n",
            "Model Number: 342 with model ETS in generation 2 of 10\n",
            "Model Number: 343 with model WindowRegression in generation 2 of 10\n",
            "Model Number: 344 with model AverageValueNaive in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:541: ConvergenceWarning:\n",
            "\n",
            "lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 345 with model Theta in generation 2 of 10\n",
            "Model Number: 346 with model UnobservedComponents in generation 2 of 10\n",
            "Model Number: 347 with model UnobservedComponents in generation 2 of 10\n",
            "Model Number: 348 with model Theta in generation 2 of 10\n",
            "Model Number: 349 with model UnivariateMotif in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 349 in generation 2: UnivariateMotif\n",
            "Model Number: 350 with model UnivariateMotif in generation 2 of 10\n",
            "Model Number: 351 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 352 with model MultivariateRegression in generation 2 of 10\n",
            "Model Number: 353 with model UnobservedComponents in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 353 in generation 2: UnobservedComponents\n",
            "Model Number: 354 with model ARIMA in generation 2 of 10\n",
            "Model Number: 355 with model LastValueNaive in generation 2 of 10\n",
            "Model Number: 356 with model Theta in generation 2 of 10\n",
            "Model Number: 357 with model UnivariateMotif in generation 2 of 10\n",
            "Model Number: 358 with model LastValueNaive in generation 2 of 10\n",
            "Model Number: 359 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 360 with model Theta in generation 2 of 10\n",
            "Model Number: 361 with model ARIMA in generation 2 of 10\n",
            "Model Number: 362 with model ARIMA in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 362 in generation 2: ARIMA\n",
            "Model Number: 363 with model NVAR in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 363 in generation 2: NVAR\n",
            "Model Number: 364 with model GLS in generation 2 of 10\n",
            "Model Number: 365 with model UnobservedComponents in generation 2 of 10\n",
            "Model Number: 366 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 367 with model UnobservedComponents in generation 2 of 10\n",
            "Model Number: 368 with model AverageValueNaive in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer MaxAbsScaler failed on fit') in model 368 in generation 2: AverageValueNaive\n",
            "Model Number: 369 with model GLM in generation 2 of 10\n",
            "Model Number: 370 with model MultivariateRegression in generation 2 of 10\n",
            "Model Number: 371 with model LastValueNaive in generation 2 of 10\n",
            "Model Number: 372 with model UnivariateMotif in generation 2 of 10\n",
            "Model Number: 373 with model MetricMotif in generation 2 of 10\n",
            "Model Number: 374 with model UnobservedComponents in generation 2 of 10\n",
            "Model Number: 375 with model Theta in generation 2 of 10\n",
            "Model Number: 376 with model FBProphet in generation 2 of 10\n",
            "Model Number: 377 with model DatepartRegression in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 377 in generation 2: DatepartRegression\n",
            "Model Number: 378 with model GLM in generation 2 of 10\n",
            "Model Number: 379 with model NVAR in generation 2 of 10\n",
            "Model Number: 380 with model ETS in generation 2 of 10\n",
            "Model Number: 381 with model ARIMA in generation 2 of 10\n",
            "Model Number: 382 with model UnivariateMotif in generation 2 of 10\n",
            "Model Number: 383 with model Theta in generation 2 of 10\n",
            "Model Number: 384 with model ETS in generation 2 of 10\n",
            "Model Number: 385 with model NVAR in generation 2 of 10\n",
            "Model Number: 386 with model ConstantNaive in generation 2 of 10\n",
            "Model Number: 387 with model ETS in generation 2 of 10\n",
            "Model Number: 388 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 389 with model UnivariateMotif in generation 2 of 10\n",
            "Model Number: 390 with model ConstantNaive in generation 2 of 10\n",
            "Model Number: 391 with model GLS in generation 2 of 10\n",
            "Model Number: 392 with model DatepartRegression in generation 2 of 10\n",
            "Model Number: 393 with model UnobservedComponents in generation 2 of 10\n",
            "Model Number: 394 with model FBProphet in generation 2 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 394 in generation 2: FBProphet\n",
            "Model Number: 395 with model UnobservedComponents in generation 2 of 10\n",
            "Model Number: 396 with model ARDL in generation 2 of 10\n",
            "Model Number: 397 with model GLM in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/generalized_linear_model.py:308: DomainWarning:\n",
            "\n",
            "The InversePower link function does not respect the domain of the Gamma family.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Template Eval Error: Exception('Transformer RobustScaler failed on inverse') in model 397 in generation 2: GLM\n",
            "Model Number: 398 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 399 with model MetricMotif in generation 2 of 10\n",
            "Model Number: 400 with model Theta in generation 2 of 10\n",
            "Model Number: 401 with model ETS in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 401 in generation 2: ETS\n",
            "Model Number: 402 with model AverageValueNaive in generation 2 of 10\n",
            "Model Number: 403 with model SectionalMotif in generation 2 of 10\n",
            "Model Number: 404 with model NVAR in generation 2 of 10\n",
            "Model Number: 405 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 406 with model GLM in generation 2 of 10\n",
            "Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 406 in generation 2: GLM\n",
            "Model Number: 407 with model Theta in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 408 with model NVAR in generation 2 of 10\n",
            "Model Number: 409 with model MetricMotif in generation 2 of 10\n",
            "Model Number: 410 with model DatepartRegression in generation 2 of 10\n",
            "Model Number: 411 with model MultivariateRegression in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 412 with model NVAR in generation 2 of 10\n",
            "Model Number: 413 with model GLM in generation 2 of 10\n",
            "Model Number: 414 with model MultivariateRegression in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 415 with model ETS in generation 2 of 10\n",
            "Model Number: 416 with model WindowRegression in generation 2 of 10\n",
            "Model Number: 417 with model AverageValueNaive in generation 2 of 10\n",
            "Model Number: 418 with model GLS in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 419 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 420 with model ARDL in generation 2 of 10\n",
            "Model Number: 421 with model NVAR in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 421 in generation 2: NVAR\n",
            "Model Number: 422 with model AverageValueNaive in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 422 in generation 2: AverageValueNaive\n",
            "Model Number: 423 with model ConstantNaive in generation 2 of 10\n",
            "Model Number: 424 with model SeasonalNaive in generation 2 of 10\n",
            "Model Number: 425 with model DatepartRegression in generation 2 of 10\n",
            "Model Number: 426 with model ARDL in generation 2 of 10\n",
            "Model Number: 427 with model MetricMotif in generation 2 of 10\n",
            "Model Number: 428 with model WindowRegression in generation 2 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 428 in generation 2: WindowRegression\n",
            "Model Number: 429 with model ARIMA in generation 2 of 10\n",
            "Model Number: 430 with model FBProphet in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 430 in generation 2: FBProphet\n",
            "Model Number: 431 with model UnivariateRegression in generation 2 of 10\n",
            "Model Number: 432 with model GLM in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 432 in generation 2: GLM\n",
            "Model Number: 433 with model AverageValueNaive in generation 2 of 10\n",
            "Model Number: 434 with model FBProphet in generation 2 of 10\n",
            "Model Number: 435 with model ConstantNaive in generation 2 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 435 in generation 2: ConstantNaive\n",
            "Model Number: 436 with model MultivariateMotif in generation 2 of 10\n",
            "New Generation: 3 of 10\n",
            "Model Number: 437 with model MultivariateRegression in generation 3 of 10\n",
            "Model Number: 438 with model SeasonalNaive in generation 3 of 10\n",
            "Model Number: 439 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 440 with model NVAR in generation 3 of 10\n",
            "Model Number: 441 with model SeasonalNaive in generation 3 of 10\n",
            "Model Number: 442 with model NVAR in generation 3 of 10\n",
            "Model Number: 443 with model ARDL in generation 3 of 10\n",
            "Model Number: 444 with model ETS in generation 3 of 10\n",
            "Model Number: 445 with model Theta in generation 3 of 10\n",
            "Model Number: 446 with model MetricMotif in generation 3 of 10\n",
            "Model Number: 447 with model MultivariateMotif in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 447 in generation 3: MultivariateMotif\n",
            "Model Number: 448 with model GLM in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 448 in generation 3: GLM\n",
            "Model Number: 449 with model FBProphet in generation 3 of 10\n",
            "Model Number: 450 with model MultivariateRegression in generation 3 of 10\n",
            "Model Number: 451 with model UnivariateRegression in generation 3 of 10\n",
            "Model Number: 452 with model NVAR in generation 3 of 10\n",
            "Model Number: 453 with model NVAR in generation 3 of 10\n",
            "Model Number: 454 with model SectionalMotif in generation 3 of 10\n",
            "Model Number: 455 with model SeasonalNaive in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 455 in generation 3: SeasonalNaive\n",
            "Model Number: 456 with model UnivariateMotif in generation 3 of 10\n",
            "Model Number: 457 with model FBProphet in generation 3 of 10\n",
            "Model Number: 458 with model FBProphet in generation 3 of 10\n",
            "Model Number: 459 with model WindowRegression in generation 3 of 10\n",
            "Model Number: 460 with model SectionalMotif in generation 3 of 10\n",
            "Model Number: 461 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 462 with model SeasonalNaive in generation 3 of 10\n",
            "Model Number: 463 with model WindowRegression in generation 3 of 10\n",
            "Model Number: 464 with model SectionalMotif in generation 3 of 10\n",
            "Model Number: 465 with model GLS in generation 3 of 10\n",
            "Model Number: 466 with model UnivariateRegression in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 466 in generation 3: UnivariateRegression\n",
            "Model Number: 467 with model FBProphet in generation 3 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 467 in generation 3: FBProphet\n",
            "Model Number: 468 with model DatepartRegression in generation 3 of 10\n",
            "Model Number: 469 with model MetricMotif in generation 3 of 10\n",
            "Model Number: 470 with model UnivariateRegression in generation 3 of 10\n",
            "Model Number: 471 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 472 with model UnobservedComponents in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 472 in generation 3: UnobservedComponents\n",
            "Model Number: 473 with model AverageValueNaive in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer QuantileTransformer failed on inverse') in model 473 in generation 3: AverageValueNaive\n",
            "Model Number: 474 with model DatepartRegression in generation 3 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 475 with model MetricMotif in generation 3 of 10\n",
            "Model Number: 476 with model DatepartRegression in generation 3 of 10\n",
            "Model Number: 477 with model UnobservedComponents in generation 3 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor supplied\") in model 477 in generation 3: UnobservedComponents\n",
            "Model Number: 478 with model ETS in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 478 in generation 3: ETS\n",
            "Model Number: 479 with model GLS in generation 3 of 10\n",
            "Model Number: 480 with model NVAR in generation 3 of 10\n",
            "Model Number: 481 with model MetricMotif in generation 3 of 10\n",
            "Model Number: 482 with model GLM in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 482 in generation 3: GLM\n",
            "Model Number: 483 with model DatepartRegression in generation 3 of 10\n",
            "Model Number: 484 with model MultivariateMotif in generation 3 of 10\n",
            "Model Number: 485 with model UnivariateRegression in generation 3 of 10\n",
            "Model Number: 486 with model MultivariateMotif in generation 3 of 10\n",
            "Model Number: 487 with model LastValueNaive in generation 3 of 10\n",
            "Model Number: 488 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 489 with model WindowRegression in generation 3 of 10\n",
            "Model Number: 490 with model ARDL in generation 3 of 10\n",
            "Model Number: 491 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 492 with model ARDL in generation 3 of 10\n",
            "Model Number: 493 with model GLM in generation 3 of 10\n",
            "Model Number: 494 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 495 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 496 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 497 with model ARDL in generation 3 of 10\n",
            "Template Eval Error: ValueError(\"ARDL series Close failed with error IndexError('tuple index out of range') exog train None and predict None\") in model 497 in generation 3: ARDL\n",
            "Model Number: 498 with model Theta in generation 3 of 10\n",
            "Model Number: 499 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 500 with model LastValueNaive in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 500 in generation 3: LastValueNaive\n",
            "Model Number: 501 with model UnivariateMotif in generation 3 of 10\n",
            "Model Number: 502 with model LastValueNaive in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer PowerTransformer failed on fit') in model 502 in generation 3: LastValueNaive\n",
            "Model Number: 503 with model FBProphet in generation 3 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 503 in generation 3: FBProphet\n",
            "Model Number: 504 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 505 with model Theta in generation 3 of 10\n",
            "Model Number: 506 with model LastValueNaive in generation 3 of 10\n",
            "Model Number: 507 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 508 with model UnobservedComponents in generation 3 of 10\n",
            "Model Number: 509 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 510 with model DatepartRegression in generation 3 of 10\n",
            "Model Number: 511 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 512 with model ARDL in generation 3 of 10\n",
            "Model Number: 513 with model MultivariateRegression in generation 3 of 10\n",
            "Template Eval Error: LightGBMError('Unknown objective type name: regression,mape') in model 513 in generation 3: MultivariateRegression\n",
            "Model Number: 514 with model UnobservedComponents in generation 3 of 10\n",
            "Model Number: 515 with model ARIMA in generation 3 of 10\n",
            "Model Number: 516 with model ARIMA in generation 3 of 10\n",
            "Model Number: 517 with model Theta in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 517 in generation 3: Theta\n",
            "Model Number: 518 with model ARIMA in generation 3 of 10\n",
            "Model Number: 519 with model UnobservedComponents in generation 3 of 10\n",
            "Model Number: 520 with model GLS in generation 3 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 521 with model Theta in generation 3 of 10\n",
            "Model Number: 522 with model Theta in generation 3 of 10\n",
            "Model Number: 523 with model UnivariateRegression in generation 3 of 10\n",
            "Model Number: 524 with model LastValueNaive in generation 3 of 10\n",
            "Model Number: 525 with model GLS in generation 3 of 10\n",
            "Model Number: 526 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 527 with model UnivariateMotif in generation 3 of 10\n",
            "Model Number: 528 with model ARIMA in generation 3 of 10\n",
            "Model Number: 529 with model AverageValueNaive in generation 3 of 10\n",
            "Model Number: 530 with model SeasonalNaive in generation 3 of 10\n",
            "Model Number: 531 with model UnobservedComponents in generation 3 of 10\n",
            "Model Number: 532 with model Theta in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer StandardScaler failed on fit') in model 532 in generation 3: Theta\n",
            "Model Number: 533 with model ETS in generation 3 of 10\n",
            "Model Number: 534 with model FBProphet in generation 3 of 10\n",
            "Model Number: 535 with model UnivariateMotif in generation 3 of 10\n",
            "Model Number: 536 with model MultivariateRegression in generation 3 of 10\n",
            "Model Number: 537 with model DatepartRegression in generation 3 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning:\n",
            "\n",
            "Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.279e-02, tolerance: 1.000e-04\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 538 with model LastValueNaive in generation 3 of 10\n",
            "Model Number: 539 with model SeasonalNaive in generation 3 of 10\n",
            "Model Number: 540 with model SeasonalNaive in generation 3 of 10\n",
            "Model Number: 541 with model FBProphet in generation 3 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 542 with model Theta in generation 3 of 10\n",
            "Model Number: 543 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 544 with model ConstantNaive in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 544 in generation 3: ConstantNaive\n",
            "Model Number: 545 with model UnobservedComponents in generation 3 of 10\n",
            "Model Number: 546 with model ARIMA in generation 3 of 10\n",
            "Model Number: 547 with model MetricMotif in generation 3 of 10\n",
            "Model Number: 548 with model MultivariateRegression in generation 3 of 10\n",
            "Model Number: 549 with model MultivariateMotif in generation 3 of 10\n",
            "Model Number: 550 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 551 with model GLM in generation 3 of 10\n",
            "Model Number: 552 with model GLS in generation 3 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:198: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 553 with model ConstantNaive in generation 3 of 10\n",
            "Model Number: 554 with model Theta in generation 3 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 554 in generation 3: Theta\n",
            "Model Number: 555 with model ETS in generation 3 of 10\n",
            "Model Number: 556 with model LastValueNaive in generation 3 of 10\n",
            "Model Number: 557 with model MultivariateRegression in generation 3 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 557 in generation 3: MultivariateRegression\n",
            "Model Number: 558 with model MultivariateMotif in generation 3 of 10\n",
            "Model Number: 559 with model NVAR in generation 3 of 10\n",
            "Model Number: 560 with model ARDL in generation 3 of 10\n",
            "Model Number: 561 with model FBProphet in generation 3 of 10\n",
            "New Generation: 4 of 10\n",
            "Model Number: 562 with model MultivariateRegression in generation 4 of 10\n",
            "Model Number: 563 with model NVAR in generation 4 of 10\n",
            "Model Number: 564 with model UnobservedComponents in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 564 in generation 4: UnobservedComponents\n",
            "Model Number: 565 with model ETS in generation 4 of 10\n",
            "Model Number: 566 with model LastValueNaive in generation 4 of 10\n",
            "Model Number: 567 with model LastValueNaive in generation 4 of 10\n",
            "Model Number: 568 with model LastValueNaive in generation 4 of 10\n",
            "Model Number: 569 with model MetricMotif in generation 4 of 10\n",
            "Model Number: 570 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 571 with model NVAR in generation 4 of 10\n",
            "Model Number: 572 with model SectionalMotif in generation 4 of 10\n",
            "Model Number: 573 with model Theta in generation 4 of 10\n",
            "Model Number: 574 with model Theta in generation 4 of 10\n",
            "Model Number: 575 with model ARIMA in generation 4 of 10\n",
            "Model Number: 576 with model MultivariateRegression in generation 4 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 576 in generation 4: MultivariateRegression\n",
            "Model Number: 577 with model MultivariateRegression in generation 4 of 10\n",
            "Model Number: 578 with model UnobservedComponents in generation 4 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor supplied\") in model 578 in generation 4: UnobservedComponents\n",
            "Model Number: 579 with model Theta in generation 4 of 10\n",
            "Model Number: 580 with model UnivariateMotif in generation 4 of 10\n",
            "Model Number: 581 with model UnobservedComponents in generation 4 of 10\n",
            "Model Number: 582 with model GLS in generation 4 of 10\n",
            "Model Number: 583 with model ARIMA in generation 4 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 584 with model ETS in generation 4 of 10\n",
            "Model Number: 585 with model ARDL in generation 4 of 10\n",
            "Model Number: 586 with model LastValueNaive in generation 4 of 10\n",
            "Model Number: 587 with model AverageValueNaive in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 587 in generation 4: AverageValueNaive\n",
            "Model Number: 588 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 589 with model ETS in generation 4 of 10\n",
            "Model Number: 590 with model SectionalMotif in generation 4 of 10\n",
            "Model Number: 591 with model FBProphet in generation 4 of 10\n",
            "Model Number: 592 with model NVAR in generation 4 of 10\n",
            "Model Number: 593 with model UnobservedComponents in generation 4 of 10\n",
            "Model Number: 594 with model GLM in generation 4 of 10\n",
            "Model Number: 595 with model SectionalMotif in generation 4 of 10\n",
            "Model Number: 596 with model ETS in generation 4 of 10\n",
            "Model Number: 597 with model AverageValueNaive in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer RobustScaler failed on fit') in model 597 in generation 4: AverageValueNaive\n",
            "Model Number: 598 with model ARDL in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 598 in generation 4: ARDL\n",
            "Model Number: 599 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 600 with model MultivariateMotif in generation 4 of 10\n",
            "Model Number: 601 with model AverageValueNaive in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 601 in generation 4: AverageValueNaive\n",
            "Model Number: 602 with model AverageValueNaive in generation 4 of 10\n",
            "Model Number: 603 with model Theta in generation 4 of 10\n",
            "Model Number: 604 with model MetricMotif in generation 4 of 10\n",
            "Model Number: 605 with model DatepartRegression in generation 4 of 10\n",
            "Model Number: 606 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 607 with model UnivariateRegression in generation 4 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 607 in generation 4: UnivariateRegression\n",
            "Model Number: 608 with model MultivariateMotif in generation 4 of 10\n",
            "Model Number: 609 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 610 with model GLS in generation 4 of 10\n",
            "Model Number: 611 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 612 with model AverageValueNaive in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer MaxAbsScaler failed on fit') in model 612 in generation 4: AverageValueNaive\n",
            "Model Number: 613 with model ARDL in generation 4 of 10\n",
            "Model Number: 614 with model UnivariateRegression in generation 4 of 10\n",
            "Model Number: 615 with model LastValueNaive in generation 4 of 10\n",
            "Model Number: 616 with model UnobservedComponents in generation 4 of 10\n",
            "Model Number: 617 with model Theta in generation 4 of 10\n",
            "Model Number: 618 with model UnobservedComponents in generation 4 of 10\n",
            "Model Number: 619 with model WindowRegression in generation 4 of 10\n",
            "Model Number: 620 with model Theta in generation 4 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 621 with model FBProphet in generation 4 of 10\n",
            "Model Number: 622 with model NVAR in generation 4 of 10\n",
            "Model Number: 623 with model FBProphet in generation 4 of 10\n",
            "Model Number: 624 with model FBProphet in generation 4 of 10\n",
            "Model Number: 625 with model NVAR in generation 4 of 10\n",
            "Model Number: 626 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 627 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 628 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 629 with model MetricMotif in generation 4 of 10\n",
            "Model Number: 630 with model ARDL in generation 4 of 10\n",
            "Model Number: 631 with model MultivariateMotif in generation 4 of 10\n",
            "Model Number: 632 with model Theta in generation 4 of 10\n",
            "Model Number: 633 with model GLS in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 633 in generation 4: GLS\n",
            "Model Number: 634 with model MetricMotif in generation 4 of 10\n",
            "Model Number: 635 with model ETS in generation 4 of 10\n",
            "Model Number: 636 with model NVAR in generation 4 of 10\n",
            "Model Number: 637 with model NVAR in generation 4 of 10\n",
            "Model Number: 638 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 639 with model ARIMA in generation 4 of 10\n",
            "Model Number: 640 with model WindowRegression in generation 4 of 10\n",
            "Model Number: 641 with model UnivariateRegression in generation 4 of 10\n",
            "Model Number: 642 with model FBProphet in generation 4 of 10\n",
            "Model Number: 643 with model NVAR in generation 4 of 10\n",
            "Model Number: 644 with model Theta in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 644 in generation 4: Theta\n",
            "Model Number: 645 with model UnivariateMotif in generation 4 of 10\n",
            "Model Number: 646 with model LastValueNaive in generation 4 of 10\n",
            "Model Number: 647 with model ARIMA in generation 4 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 648 with model ARDL in generation 4 of 10\n",
            "Model Number: 649 with model AverageValueNaive in generation 4 of 10\n",
            "Model Number: 650 with model DatepartRegression in generation 4 of 10\n",
            "Model Number: 651 with model UnivariateRegression in generation 4 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_coordinate_descent.py:2418: ConvergenceWarning:\n",
            "\n",
            "Objective did not converge. You might want to increase the number of iterations. Duality gap: 74455996218.80765, tolerance: 116312033.11685696\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 652 with model MultivariateRegression in generation 4 of 10\n",
            "Model Number: 653 with model MultivariateRegression in generation 4 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 653 in generation 4: MultivariateRegression\n",
            "Model Number: 654 with model AverageValueNaive in generation 4 of 10\n",
            "Model Number: 655 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 656 with model NVAR in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 656 in generation 4: NVAR\n",
            "Model Number: 657 with model UnobservedComponents in generation 4 of 10\n",
            "Model Number: 658 with model ARDL in generation 4 of 10\n",
            "Model Number: 659 with model FBProphet in generation 4 of 10\n",
            "Model Number: 660 with model LastValueNaive in generation 4 of 10\n",
            "Model Number: 661 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 662 with model ARIMA in generation 4 of 10\n",
            "Model Number: 663 with model ConstantNaive in generation 4 of 10\n",
            "Template Eval Error: ValueError(\"Model returned NaN due to a preprocessing transformer {'fillna': 'pchip', 'transformations': {'0': 'HolidayTransformer', '1': 'ScipyFilter', '2': 'RobustScaler', '3': 'AlignLastValue'}, 'transformation_params': {'0': {'threshold': 0.9, 'splash_threshold': None, 'use_dayofmonth_holidays': True, 'use_wkdom_holidays': True, 'use_wkdeom_holidays': False, 'use_lunar_holidays': False, 'use_lunar_weekday': False, 'use_islamic_holidays': False, 'use_hebrew_holidays': False, 'anomaly_detector_params': {'method': 'IQR', 'method_params': {'iqr_threshold': 2.0, 'iqr_quantiles': [0.25, 0.75]}, 'fillna': 'linear', 'transform_dict': None, 'isolated_only': False}, 'remove_excess_anomalies': True, 'impact': 'regression', 'regression_params': {}}, '1': {'method': 'savgol_filter', 'method_args': {'window_length': 91, 'polyorder': 4, 'deriv': 0, 'mode': 'mirror'}}, '2': {}, '3': {'rows': 1, 'lag': 1, 'method': 'multiplicative', 'strength': 1.0, 'first_value_only': False}}}. fail_on_forecast_nan=True\") in model 663 in generation 4: ConstantNaive\n",
            "Model Number: 664 with model FBProphet in generation 4 of 10\n",
            "Model Number: 665 with model SeasonalNaive in generation 4 of 10\n",
            "Model Number: 666 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 667 with model ETS in generation 4 of 10\n",
            "Model Number: 668 with model MetricMotif in generation 4 of 10\n",
            "Model Number: 669 with model AverageValueNaive in generation 4 of 10\n",
            "Model Number: 670 with model UnobservedComponents in generation 4 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor supplied\") in model 670 in generation 4: UnobservedComponents\n",
            "Model Number: 671 with model DatepartRegression in generation 4 of 10\n",
            "Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 671 in generation 4: DatepartRegression\n",
            "Model Number: 672 with model MetricMotif in generation 4 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_regression.py:494: UserWarning:\n",
            "\n",
            "One or more samples have no neighbors within specified radius; predicting NaN.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 673 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 674 with model Theta in generation 4 of 10\n",
            "Model Number: 675 with model UnivariateRegression in generation 4 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 675 in generation 4: UnivariateRegression\n",
            "Model Number: 676 with model MultivariateMotif in generation 4 of 10\n",
            "Model Number: 677 with model ConstantNaive in generation 4 of 10\n",
            "Model Number: 678 with model UnobservedComponents in generation 4 of 10\n",
            "Model Number: 679 with model DatepartRegression in generation 4 of 10\n",
            "Model Number: 680 with model ARIMA in generation 4 of 10\n",
            "Model Number: 681 with model LastValueNaive in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 681 in generation 4: LastValueNaive\n",
            "Model Number: 682 with model NVAR in generation 4 of 10\n",
            "Model Number: 683 with model UnobservedComponents in generation 4 of 10\n",
            "Model Number: 684 with model AverageValueNaive in generation 4 of 10\n",
            "Template Eval Error: Exception('Transformer RobustScaler failed on fit') in model 684 in generation 4: AverageValueNaive\n",
            "Model Number: 685 with model UnivariateMotif in generation 4 of 10\n",
            "Model Number: 686 with model FBProphet in generation 4 of 10\n",
            "New Generation: 5 of 10\n",
            "Model Number: 687 with model NVAR in generation 5 of 10\n",
            "Model Number: 688 with model SectionalMotif in generation 5 of 10\n",
            "Model Number: 689 with model SeasonalNaive in generation 5 of 10\n",
            "Model Number: 690 with model UnivariateMotif in generation 5 of 10\n",
            "Model Number: 691 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 692 with model MetricMotif in generation 5 of 10\n",
            "Model Number: 693 with model ARDL in generation 5 of 10\n",
            "Model Number: 694 with model ARDL in generation 5 of 10\n",
            "Model Number: 695 with model GLS in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:541: ConvergenceWarning:\n",
            "\n",
            "lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 696 with model UnobservedComponents in generation 5 of 10\n",
            "Model Number: 697 with model ARDL in generation 5 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but future_regressor not supplied\") in model 697 in generation 5: ARDL\n",
            "Model Number: 698 with model Theta in generation 5 of 10\n",
            "Model Number: 699 with model ETS in generation 5 of 10\n",
            "Model Number: 700 with model FBProphet in generation 5 of 10\n",
            "Model Number: 701 with model DatepartRegression in generation 5 of 10\n",
            "Model Number: 702 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 703 with model ETS in generation 5 of 10\n",
            "Model Number: 704 with model MultivariateRegression in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 705 with model GLM in generation 5 of 10\n",
            "Model Number: 706 with model MultivariateRegression in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 707 with model UnobservedComponents in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 708 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 709 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 710 with model Theta in generation 5 of 10\n",
            "Model Number: 711 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 712 with model ARDL in generation 5 of 10\n",
            "Model Number: 713 with model UnobservedComponents in generation 5 of 10\n",
            "Model Number: 714 with model GLS in generation 5 of 10\n",
            "Model Number: 715 with model GLS in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:541: ConvergenceWarning:\n",
            "\n",
            "lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 716 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 717 with model ARDL in generation 5 of 10\n",
            "Model Number: 718 with model FBProphet in generation 5 of 10\n",
            "Model Number: 719 with model ETS in generation 5 of 10\n",
            "Model Number: 720 with model ETS in generation 5 of 10\n",
            "Model Number: 721 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 722 with model MultivariateMotif in generation 5 of 10\n",
            "Model Number: 723 with model FBProphet in generation 5 of 10\n",
            "Model Number: 724 with model Theta in generation 5 of 10\n",
            "Model Number: 725 with model MultivariateRegression in generation 5 of 10\n",
            "Model Number: 726 with model UnivariateRegression in generation 5 of 10\n",
            "Model Number: 727 with model NVAR in generation 5 of 10\n",
            "Model Number: 728 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 729 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 730 with model Theta in generation 5 of 10\n",
            "Model Number: 731 with model NVAR in generation 5 of 10\n",
            "Model Number: 732 with model UnobservedComponents in generation 5 of 10\n",
            "Model Number: 733 with model ARIMA in generation 5 of 10\n",
            "Model Number: 734 with model UnobservedComponents in generation 5 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 734 in generation 5: UnobservedComponents\n",
            "Model Number: 735 with model DatepartRegression in generation 5 of 10\n",
            "Model Number: 736 with model Theta in generation 5 of 10\n",
            "Model Number: 737 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 738 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 739 with model UnobservedComponents in generation 5 of 10\n",
            "Model Number: 740 with model Theta in generation 5 of 10\n",
            "Model Number: 741 with model ARIMA in generation 5 of 10\n",
            "Model Number: 742 with model Theta in generation 5 of 10\n",
            "Model Number: 743 with model UnobservedComponents in generation 5 of 10\n",
            "Model Number: 744 with model SeasonalNaive in generation 5 of 10\n",
            "Model Number: 745 with model ETS in generation 5 of 10\n",
            "Model Number: 746 with model GLM in generation 5 of 10\n",
            "Model Number: 747 with model Theta in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 748 with model SeasonalNaive in generation 5 of 10\n",
            "Model Number: 749 with model UnivariateMotif in generation 5 of 10\n",
            "Model Number: 750 with model DatepartRegression in generation 5 of 10\n",
            "Model Number: 751 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 752 with model ETS in generation 5 of 10\n",
            "Model Number: 753 with model FBProphet in generation 5 of 10\n",
            "Model Number: 754 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 755 with model FBProphet in generation 5 of 10\n",
            "Model Number: 756 with model SeasonalNaive in generation 5 of 10\n",
            "Model Number: 757 with model NVAR in generation 5 of 10\n",
            "Model Number: 758 with model ARIMA in generation 5 of 10\n",
            "Model Number: 759 with model Theta in generation 5 of 10\n",
            "Model Number: 760 with model MultivariateRegression in generation 5 of 10\n",
            "Model Number: 761 with model ConstantNaive in generation 5 of 10\n",
            "Model Number: 762 with model ARIMA in generation 5 of 10\n",
            "Model Number: 763 with model MetricMotif in generation 5 of 10\n",
            "Model Number: 764 with model SeasonalNaive in generation 5 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 764 in generation 5: SeasonalNaive\n",
            "Model Number: 765 with model MultivariateRegression in generation 5 of 10\n",
            "Model Number: 766 with model NVAR in generation 5 of 10\n",
            "Model Number: 767 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 768 with model Theta in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 769 with model AverageValueNaive in generation 5 of 10\n",
            "Model Number: 770 with model ConstantNaive in generation 5 of 10\n",
            "Model Number: 771 with model MultivariateRegression in generation 5 of 10\n",
            "Model Number: 772 with model NVAR in generation 5 of 10\n",
            "Model Number: 773 with model ARIMA in generation 5 of 10\n",
            "Model Number: 774 with model UnivariateRegression in generation 5 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 774 in generation 5: UnivariateRegression\n",
            "Model Number: 775 with model MetricMotif in generation 5 of 10\n",
            "Model Number: 776 with model ARDL in generation 5 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 776 in generation 5: ARDL\n",
            "Model Number: 777 with model LastValueNaive in generation 5 of 10\n",
            "Model Number: 778 with model MultivariateRegression in generation 5 of 10\n",
            "Template Eval Error: LightGBMError('[gamma]: at least one target label is negative') in model 778 in generation 5: MultivariateRegression\n",
            "Model Number: 779 with model ARDL in generation 5 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py:1143: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 780 with model SectionalMotif in generation 5 of 10\n",
            "Model Number: 781 with model MultivariateMotif in generation 5 of 10\n",
            "Model Number: 782 with model NVAR in generation 5 of 10\n",
            "Model Number: 783 with model FBProphet in generation 5 of 10\n",
            "Model Number: 784 with model FBProphet in generation 5 of 10\n",
            "Model Number: 785 with model MultivariateRegression in generation 5 of 10\n",
            "Model Number: 786 with model FBProphet in generation 5 of 10\n",
            "No anomalies detected.\n",
            "New Generation: 6 of 10\n",
            "Model Number: 787 with model ETS in generation 6 of 10\n",
            "Model Number: 788 with model ConstantNaive in generation 6 of 10\n",
            "Model Number: 789 with model DatepartRegression in generation 6 of 10\n",
            "Model Number: 790 with model UnobservedComponents in generation 6 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 791 with model MetricMotif in generation 6 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 791 in generation 6: MetricMotif\n",
            "Model Number: 792 with model ARDL in generation 6 of 10\n",
            "Model Number: 793 with model SeasonalNaive in generation 6 of 10\n",
            "Model Number: 794 with model FBProphet in generation 6 of 10\n",
            "Template Eval Error: Exception('Transformer RobustScaler failed on fit') in model 794 in generation 6: FBProphet\n",
            "Model Number: 795 with model ARDL in generation 6 of 10\n",
            "Model Number: 796 with model ConstantNaive in generation 6 of 10\n",
            "Model Number: 797 with model Theta in generation 6 of 10\n",
            "Model Number: 798 with model GLM in generation 6 of 10\n",
            "Model Number: 799 with model GLM in generation 6 of 10\n",
            "Model Number: 800 with model AverageValueNaive in generation 6 of 10\n",
            "Template Eval Error: Exception('Transformer StandardScaler failed on inverse') in model 800 in generation 6: AverageValueNaive\n",
            "Model Number: 801 with model FBProphet in generation 6 of 10\n",
            "Model Number: 802 with model SeasonalNaive in generation 6 of 10\n",
            "Model Number: 803 with model NVAR in generation 6 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 803 in generation 6: NVAR\n",
            "Model Number: 804 with model UnobservedComponents in generation 6 of 10\n",
            "Model Number: 805 with model ARDL in generation 6 of 10\n",
            "Model Number: 806 with model ARIMA in generation 6 of 10\n",
            "Model Number: 807 with model UnobservedComponents in generation 6 of 10\n",
            "Model Number: 808 with model Theta in generation 6 of 10\n",
            "Model Number: 809 with model NVAR in generation 6 of 10\n",
            "Model Number: 810 with model GLS in generation 6 of 10\n",
            "Model Number: 811 with model DatepartRegression in generation 6 of 10\n",
            "Model Number: 812 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 813 with model ConstantNaive in generation 6 of 10\n",
            "Model Number: 814 with model DatepartRegression in generation 6 of 10\n",
            "Model Number: 815 with model NVAR in generation 6 of 10\n",
            "Model Number: 816 with model FBProphet in generation 6 of 10\n",
            "Model Number: 817 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 818 with model UnobservedComponents in generation 6 of 10\n",
            "Model Number: 819 with model NVAR in generation 6 of 10\n",
            "Model Number: 820 with model Theta in generation 6 of 10\n",
            "Model Number: 821 with model UnivariateRegression in generation 6 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 821 in generation 6: UnivariateRegression\n",
            "Model Number: 822 with model ARDL in generation 6 of 10\n",
            "Model Number: 823 with model Theta in generation 6 of 10\n",
            "Model Number: 824 with model SeasonalNaive in generation 6 of 10\n",
            "Model Number: 825 with model SectionalMotif in generation 6 of 10\n",
            "Model Number: 826 with model ARDL in generation 6 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but future_regressor not supplied\") in model 826 in generation 6: ARDL\n",
            "Model Number: 827 with model MultivariateRegression in generation 6 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 828 with model GLS in generation 6 of 10\n",
            "Model Number: 829 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 830 with model SeasonalNaive in generation 6 of 10\n",
            "Model Number: 831 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 832 with model ARIMA in generation 6 of 10\n",
            "Model Number: 833 with model AverageValueNaive in generation 6 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_ridge.py:216: LinAlgWarning:\n",
            "\n",
            "Ill-conditioned matrix (rcond=1.52185e-25): result may not be accurate.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 834 with model UnivariateMotif in generation 6 of 10\n",
            "Model Number: 835 with model MetricMotif in generation 6 of 10\n",
            "Model Number: 836 with model UnivariateRegression in generation 6 of 10\n",
            "Model Number: 837 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 838 with model AverageValueNaive in generation 6 of 10\n",
            "Model Number: 839 with model SeasonalNaive in generation 6 of 10\n",
            "Model Number: 840 with model ConstantNaive in generation 6 of 10\n",
            "Model Number: 841 with model WindowRegression in generation 6 of 10\n",
            "Model Number: 842 with model MultivariateRegression in generation 6 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 842 in generation 6: MultivariateRegression\n",
            "Model Number: 843 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 844 with model FBProphet in generation 6 of 10\n",
            "Model Number: 845 with model UnobservedComponents in generation 6 of 10\n",
            "Model Number: 846 with model ARDL in generation 6 of 10\n",
            "Model Number: 847 with model GLS in generation 6 of 10\n",
            "Model Number: 848 with model FBProphet in generation 6 of 10\n",
            "Model Number: 849 with model ConstantNaive in generation 6 of 10\n",
            "Model Number: 850 with model NVAR in generation 6 of 10\n",
            "Model Number: 851 with model Theta in generation 6 of 10\n",
            "Model Number: 852 with model ARDL in generation 6 of 10\n",
            "Model Number: 853 with model SectionalMotif in generation 6 of 10\n",
            "Model Number: 854 with model ConstantNaive in generation 6 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 854 in generation 6: ConstantNaive\n",
            "Model Number: 855 with model UnivariateMotif in generation 6 of 10\n",
            "Model Number: 856 with model ConstantNaive in generation 6 of 10\n",
            "Model Number: 857 with model UnivariateRegression in generation 6 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_ridge.py:216: LinAlgWarning:\n",
            "\n",
            "Ill-conditioned matrix (rcond=1.22736e-39): result may not be accurate.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 858 with model UnobservedComponents in generation 6 of 10\n",
            "Model Number: 859 with model ARIMA in generation 6 of 10\n",
            "Model Number: 860 with model UnivariateRegression in generation 6 of 10\n",
            "Model Number: 861 with model MultivariateRegression in generation 6 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 862 with model GLS in generation 6 of 10\n",
            "Model Number: 863 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 864 with model AverageValueNaive in generation 6 of 10\n",
            "Model Number: 865 with model UnivariateRegression in generation 6 of 10\n",
            "Model Number: 866 with model FBProphet in generation 6 of 10\n",
            "Model Number: 867 with model ARIMA in generation 6 of 10\n",
            "Model Number: 868 with model MultivariateRegression in generation 6 of 10\n",
            "Model Number: 869 with model ConstantNaive in generation 6 of 10\n",
            "Model Number: 870 with model ARDL in generation 6 of 10\n",
            "Model Number: 871 with model ARIMA in generation 6 of 10\n",
            "Model Number: 872 with model GLS in generation 6 of 10\n",
            "Model Number: 873 with model ARIMA in generation 6 of 10\n",
            "Model Number: 874 with model MetricMotif in generation 6 of 10\n",
            "Model Number: 875 with model Theta in generation 6 of 10\n",
            "Model Number: 876 with model ETS in generation 6 of 10\n",
            "Model Number: 877 with model ARDL in generation 6 of 10\n",
            "Model Number: 878 with model SeasonalNaive in generation 6 of 10\n",
            "Model Number: 879 with model ARIMA in generation 6 of 10\n",
            "Model Number: 880 with model NVAR in generation 6 of 10\n",
            "Model Number: 881 with model Theta in generation 6 of 10\n",
            "Model Number: 882 with model UnivariateMotif in generation 6 of 10\n",
            "Model Number: 883 with model SectionalMotif in generation 6 of 10\n",
            "Model Number: 884 with model GLS in generation 6 of 10\n",
            "Model Number: 885 with model LastValueNaive in generation 6 of 10\n",
            "Model Number: 886 with model MetricMotif in generation 6 of 10\n",
            "Template Eval Error: IndexError('index 100 is out of bounds for axis 0 with size 100') in model 886 in generation 6: MetricMotif\n",
            "New Generation: 7 of 10\n",
            "Model Number: 887 with model ARDL in generation 7 of 10\n",
            "Model Number: 888 with model LastValueNaive in generation 7 of 10\n",
            "Model Number: 889 with model UnivariateMotif in generation 7 of 10\n",
            "Model Number: 890 with model UnobservedComponents in generation 7 of 10\n",
            "Model Number: 891 with model MetricMotif in generation 7 of 10\n",
            "Model Number: 892 with model SeasonalNaive in generation 7 of 10\n",
            "Model Number: 893 with model LastValueNaive in generation 7 of 10\n",
            "Model Number: 894 with model FBProphet in generation 7 of 10\n",
            "Model Number: 895 with model MultivariateRegression in generation 7 of 10\n",
            "Model Number: 896 with model Theta in generation 7 of 10\n",
            "Model Number: 897 with model SeasonalNaive in generation 7 of 10\n",
            "Model Number: 898 with model UnobservedComponents in generation 7 of 10\n",
            "Model Number: 899 with model ARDL in generation 7 of 10\n",
            "Model Number: 900 with model UnobservedComponents in generation 7 of 10\n",
            "Model Number: 901 with model ARDL in generation 7 of 10\n",
            "Model Number: 902 with model UnobservedComponents in generation 7 of 10\n",
            "Model Number: 903 with model NVAR in generation 7 of 10\n",
            "Model Number: 904 with model LastValueNaive in generation 7 of 10\n",
            "Model Number: 905 with model NVAR in generation 7 of 10\n",
            "Model Number: 906 with model MultivariateRegression in generation 7 of 10\n",
            "Model Number: 907 with model GLM in generation 7 of 10\n",
            "Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 907 in generation 7: GLM\n",
            "Model Number: 908 with model ETS in generation 7 of 10\n",
            "Model Number: 909 with model SeasonalNaive in generation 7 of 10\n",
            "Model Number: 910 with model LastValueNaive in generation 7 of 10\n",
            "Template Eval Error: Exception('Transformer PowerTransformer failed on inverse') in model 910 in generation 7: LastValueNaive\n",
            "Model Number: 911 with model ETS in generation 7 of 10\n",
            "Model Number: 912 with model DatepartRegression in generation 7 of 10\n",
            "Model Number: 913 with model MultivariateRegression in generation 7 of 10\n",
            "Model Number: 914 with model ARIMA in generation 7 of 10\n",
            "Model Number: 915 with model ETS in generation 7 of 10\n",
            "Model Number: 916 with model UnivariateRegression in generation 7 of 10\n",
            "Model Number: 917 with model MultivariateRegression in generation 7 of 10\n",
            "Model Number: 918 with model DatepartRegression in generation 7 of 10\n",
            "Model Number: 919 with model ARDL in generation 7 of 10\n",
            "Model Number: 920 with model Theta in generation 7 of 10\n",
            "Model Number: 921 with model WindowRegression in generation 7 of 10\n",
            "Model Number: 922 with model MetricMotif in generation 7 of 10\n",
            "Model Number: 923 with model AverageValueNaive in generation 7 of 10\n",
            "Model Number: 924 with model AverageValueNaive in generation 7 of 10\n",
            "Model Number: 925 with model FBProphet in generation 7 of 10\n",
            "Model Number: 926 with model FBProphet in generation 7 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 926 in generation 7: FBProphet\n",
            "Model Number: 927 with model MetricMotif in generation 7 of 10\n",
            "Model Number: 928 with model ARDL in generation 7 of 10\n",
            "Model Number: 929 with model SectionalMotif in generation 7 of 10\n",
            "Template Eval Error: ValueError(\"regression_type=='User' but no future_regressor supplied\") in model 929 in generation 7: SectionalMotif\n",
            "Model Number: 930 with model Theta in generation 7 of 10\n",
            "Model Number: 931 with model GLS in generation 7 of 10\n",
            "Model Number: 932 with model NVAR in generation 7 of 10\n",
            "Model Number: 933 with model ETS in generation 7 of 10\n",
            "Model Number: 934 with model GLS in generation 7 of 10\n",
            "Model Number: 935 with model GLS in generation 7 of 10\n",
            "Model Number: 936 with model SeasonalNaive in generation 7 of 10\n",
            "Model Number: 937 with model Theta in generation 7 of 10\n",
            "Model Number: 938 with model ARDL in generation 7 of 10\n",
            "Model Number: 939 with model LastValueNaive in generation 7 of 10\n",
            "Model Number: 940 with model Theta in generation 7 of 10\n",
            "Model Number: 941 with model Theta in generation 7 of 10\n",
            "Model Number: 942 with model ARDL in generation 7 of 10\n",
            "Model Number: 943 with model SeasonalNaive in generation 7 of 10\n",
            "Model Number: 944 with model AverageValueNaive in generation 7 of 10\n",
            "Model Number: 945 with model GLM in generation 7 of 10\n",
            "Model Number: 946 with model UnobservedComponents in generation 7 of 10\n",
            "Model Number: 947 with model AverageValueNaive in generation 7 of 10\n",
            "Model Number: 948 with model ConstantNaive in generation 7 of 10\n",
            "Model Number: 949 with model ARIMA in generation 7 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 950 with model UnobservedComponents in generation 7 of 10\n",
            "Model Number: 951 with model AverageValueNaive in generation 7 of 10\n",
            "Model Number: 952 with model NVAR in generation 7 of 10\n",
            "Model Number: 953 with model SeasonalNaive in generation 7 of 10\n",
            "Model Number: 954 with model Theta in generation 7 of 10\n",
            "Model Number: 955 with model LastValueNaive in generation 7 of 10\n",
            "Model Number: 956 with model SectionalMotif in generation 7 of 10\n",
            "Model Number: 957 with model ConstantNaive in generation 7 of 10\n",
            "Model Number: 958 with model ARDL in generation 7 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 958 in generation 7: ARDL\n",
            "Model Number: 959 with model ConstantNaive in generation 7 of 10\n",
            "Model Number: 960 with model FBProphet in generation 7 of 10\n",
            "Model Number: 961 with model UnivariateMotif in generation 7 of 10\n",
            "Model Number: 962 with model ConstantNaive in generation 7 of 10\n",
            "Model Number: 963 with model MultivariateMotif in generation 7 of 10\n",
            "Model Number: 964 with model UnivariateMotif in generation 7 of 10\n",
            "Model Number: 965 with model FBProphet in generation 7 of 10\n",
            "Model Number: 966 with model SeasonalNaive in generation 7 of 10\n",
            "Template Eval Error: Exception('Transformer MinMaxScaler failed on fit') in model 966 in generation 7: SeasonalNaive\n",
            "Model Number: 967 with model LastValueNaive in generation 7 of 10\n",
            "Model Number: 968 with model NVAR in generation 7 of 10\n",
            "Model Number: 969 with model Theta in generation 7 of 10\n",
            "Model Number: 970 with model ConstantNaive in generation 7 of 10\n",
            "Model Number: 971 with model LastValueNaive in generation 7 of 10\n",
            "Template Eval Error: Exception('Transformer Detrend failed on fit') in model 971 in generation 7: LastValueNaive\n",
            "Model Number: 972 with model GLS in generation 7 of 10\n",
            "Model Number: 973 with model ETS in generation 7 of 10\n",
            "Model Number: 974 with model Theta in generation 7 of 10\n",
            "Model Number: 975 with model Theta in generation 7 of 10\n",
            "Model Number: 976 with model DatepartRegression in generation 7 of 10\n",
            "Model Number: 977 with model UnobservedComponents in generation 7 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor supplied\") in model 977 in generation 7: UnobservedComponents\n",
            "Model Number: 978 with model UnivariateRegression in generation 7 of 10\n",
            "Model Number: 979 with model SeasonalNaive in generation 7 of 10\n",
            "Model Number: 980 with model ConstantNaive in generation 7 of 10\n",
            "Model Number: 981 with model MultivariateRegression in generation 7 of 10\n",
            "Model Number: 982 with model DatepartRegression in generation 7 of 10\n",
            "Model Number: 983 with model UnivariateRegression in generation 7 of 10\n",
            "Model Number: 984 with model UnivariateMotif in generation 7 of 10\n",
            "Model Number: 985 with model GLS in generation 7 of 10\n",
            "Model Number: 986 with model Theta in generation 7 of 10\n",
            "New Generation: 8 of 10\n",
            "Model Number: 987 with model ARDL in generation 8 of 10\n",
            "Model Number: 988 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 989 with model MultivariateRegression in generation 8 of 10\n",
            "Model Number: 990 with model ARIMA in generation 8 of 10\n",
            "Model Number: 991 with model ConstantNaive in generation 8 of 10\n",
            "Model Number: 992 with model FBProphet in generation 8 of 10\n",
            "Model Number: 993 with model UnivariateRegression in generation 8 of 10\n",
            "Model Number: 994 with model GLM in generation 8 of 10\n",
            "Model Number: 995 with model Theta in generation 8 of 10\n",
            "Model Number: 996 with model SeasonalNaive in generation 8 of 10\n",
            "Model Number: 997 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 998 with model ConstantNaive in generation 8 of 10\n",
            "Model Number: 999 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 1000 with model UnobservedComponents in generation 8 of 10\n",
            "Model Number: 1001 with model UnivariateRegression in generation 8 of 10\n",
            "Model Number: 1002 with model MetricMotif in generation 8 of 10\n",
            "Model Number: 1003 with model ARDL in generation 8 of 10\n",
            "Template Eval Error: ValueError(\"ARDL series Close failed with error IndexError('tuple index out of range') exog train None and predict None\") in model 1003 in generation 8: ARDL\n",
            "Model Number: 1004 with model Theta in generation 8 of 10\n",
            "Model Number: 1005 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 1006 with model NVAR in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1006 in generation 8: NVAR\n",
            "Model Number: 1007 with model LastValueNaive in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 1007 in generation 8: LastValueNaive\n",
            "Model Number: 1008 with model AverageValueNaive in generation 8 of 10\n",
            "Model Number: 1009 with model SeasonalNaive in generation 8 of 10\n",
            "Model Number: 1010 with model ConstantNaive in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer QuantileTransformer failed on inverse') in model 1010 in generation 8: ConstantNaive\n",
            "Model Number: 1011 with model UnobservedComponents in generation 8 of 10\n",
            "Model Number: 1012 with model MultivariateRegression in generation 8 of 10\n",
            "Model Number: 1013 with model MetricMotif in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 1013 in generation 8: MetricMotif\n",
            "Model Number: 1014 with model GLS in generation 8 of 10\n",
            "Model Number: 1015 with model SeasonalNaive in generation 8 of 10\n",
            "Model Number: 1016 with model GLM in generation 8 of 10\n",
            "Model Number: 1017 with model UnivariateMotif in generation 8 of 10\n",
            "Model Number: 1018 with model ARDL in generation 8 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1019 with model UnivariateRegression in generation 8 of 10\n",
            "Model Number: 1020 with model MultivariateMotif in generation 8 of 10\n",
            "Model Number: 1021 with model ETS in generation 8 of 10\n",
            "Model Number: 1022 with model NVAR in generation 8 of 10\n",
            "Model Number: 1023 with model ETS in generation 8 of 10\n",
            "Model Number: 1024 with model SeasonalNaive in generation 8 of 10\n",
            "Model Number: 1025 with model ConstantNaive in generation 8 of 10\n",
            "Model Number: 1026 with model Theta in generation 8 of 10\n",
            "Model Number: 1027 with model NVAR in generation 8 of 10\n",
            "Model Number: 1028 with model MultivariateRegression in generation 8 of 10\n",
            "Model Number: 1029 with model SectionalMotif in generation 8 of 10\n",
            "Model Number: 1030 with model ETS in generation 8 of 10\n",
            "Model Number: 1031 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 1032 with model ARIMA in generation 8 of 10\n",
            "Model Number: 1033 with model UnivariateRegression in generation 8 of 10\n",
            "Model Number: 1034 with model MultivariateRegression in generation 8 of 10\n",
            "Model Number: 1035 with model FBProphet in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 1035 in generation 8: FBProphet\n",
            "Model Number: 1036 with model UnivariateMotif in generation 8 of 10\n",
            "Model Number: 1037 with model ARDL in generation 8 of 10\n",
            "Model Number: 1038 with model SeasonalNaive in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1038 in generation 8: SeasonalNaive\n",
            "Model Number: 1039 with model ARDL in generation 8 of 10\n",
            "Model Number: 1040 with model SectionalMotif in generation 8 of 10\n",
            "Model Number: 1041 with model MetricMotif in generation 8 of 10\n",
            "Model Number: 1042 with model UnivariateRegression in generation 8 of 10\n",
            "Model Number: 1043 with model SectionalMotif in generation 8 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_coordinate_descent.py:2418: ConvergenceWarning:\n",
            "\n",
            "Objective did not converge. You might want to increase the number of iterations. Duality gap: 15697467388.552309, tolerance: 4381182.810278471\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1044 with model AverageValueNaive in generation 8 of 10\n",
            "Model Number: 1045 with model MultivariateRegression in generation 8 of 10\n",
            "Template Eval Error: XGBoostError('[22:12:02] /workspace/src/objective/regression_obj.cu:343: PoissonRegression: label must be nonnegative\\nStack trace:\\n  [bt] (0) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0xa8dc0a) [0x794513eafc0a]\\n  [bt] (1) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0xaa0797) [0x794513ec2797]\\n  [bt] (2) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x55f9ed) [0x7945139819ed]\\n  [bt] (3) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x4900d1) [0x7945138b20d1]\\n  [bt] (4) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x4c0716) [0x7945138e2716]\\n  [bt] (5) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(+0x4c5274) [0x7945138e7274]\\n  [bt] (6) /usr/local/lib/python3.10/dist-packages/xgboost/lib/libxgboost.so(XGBoosterUpdateOneIter+0x70) [0x794513583ef0]\\n  [bt] (7) /lib/x86_64-linux-gnu/libffi.so.8(+0x7e2e) [0x7945f242ce2e]\\n  [bt] (8) /lib/x86_64-linux-gnu/libffi.so.8(+0x4493) [0x7945f2429493]\\n\\n') in model 1045 in generation 8: MultivariateRegression\n",
            "Model Number: 1046 with model ARIMA in generation 8 of 10\n",
            "Model Number: 1047 with model UnivariateMotif in generation 8 of 10\n",
            "Model Number: 1048 with model ETS in generation 8 of 10\n",
            "Model Number: 1049 with model FBProphet in generation 8 of 10\n",
            "Model Number: 1050 with model UnivariateRegression in generation 8 of 10\n",
            "Model Number: 1051 with model UnobservedComponents in generation 8 of 10\n",
            "Model Number: 1052 with model UnobservedComponents in generation 8 of 10\n",
            "Model Number: 1053 with model UnobservedComponents in generation 8 of 10\n",
            "Model Number: 1054 with model ARIMA in generation 8 of 10\n",
            "Model Number: 1055 with model UnivariateMotif in generation 8 of 10\n",
            "Template Eval Error: ValueError('kth(=100) out of bounds (61)') in model 1055 in generation 8: UnivariateMotif\n",
            "Model Number: 1056 with model ARDL in generation 8 of 10\n",
            "Model Number: 1057 with model MultivariateRegression in generation 8 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but not future_regressor supplied.\") in model 1057 in generation 8: MultivariateRegression\n",
            "Model Number: 1058 with model Theta in generation 8 of 10\n",
            "Model Number: 1059 with model NVAR in generation 8 of 10\n",
            "Model Number: 1060 with model FBProphet in generation 8 of 10\n",
            "Model Number: 1061 with model DatepartRegression in generation 8 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor passed\") in model 1061 in generation 8: DatepartRegression\n",
            "Model Number: 1062 with model AverageValueNaive in generation 8 of 10\n",
            "Model Number: 1063 with model FBProphet in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 1063 in generation 8: FBProphet\n",
            "Model Number: 1064 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 1065 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 1066 with model ARDL in generation 8 of 10\n",
            "Model Number: 1067 with model GLS in generation 8 of 10\n",
            "Model Number: 1068 with model Theta in generation 8 of 10\n",
            "Model Number: 1069 with model UnobservedComponents in generation 8 of 10\n",
            "Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1069 in generation 8: UnobservedComponents\n",
            "Model Number: 1070 with model SeasonalNaive in generation 8 of 10\n",
            "Model Number: 1071 with model NVAR in generation 8 of 10\n",
            "Model Number: 1072 with model UnivariateMotif in generation 8 of 10\n",
            "Model Number: 1073 with model UnobservedComponents in generation 8 of 10\n",
            "Model Number: 1074 with model ARDL in generation 8 of 10\n",
            "Model Number: 1075 with model ConstantNaive in generation 8 of 10\n",
            "Model Number: 1076 with model GLM in generation 8 of 10\n",
            "Model Number: 1077 with model ARDL in generation 8 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1078 with model MultivariateRegression in generation 8 of 10\n",
            "Model Number: 1079 with model ARIMA in generation 8 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/autots/tools/fast_kalman.py:1306: RuntimeWarning:\n",
            "\n",
            "overflow encountered in matmul\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/autots/tools/fast_kalman.py:1293: RuntimeWarning:\n",
            "\n",
            "overflow encountered in matmul\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/autots/tools/fast_kalman.py:1306: RuntimeWarning:\n",
            "\n",
            "invalid value encountered in matmul\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/autots/tools/fast_kalman.py:1293: RuntimeWarning:\n",
            "\n",
            "invalid value encountered in matmul\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/autots/tools/fast_kalman.py:1311: RuntimeWarning:\n",
            "\n",
            "overflow encountered in multiply\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1080 with model MetricMotif in generation 8 of 10\n",
            "Template Eval Error: TypeError(\"'NoneType' object is not subscriptable\") in model 1080 in generation 8: MetricMotif\n",
            "Model Number: 1081 with model AverageValueNaive in generation 8 of 10\n",
            "Model Number: 1082 with model LastValueNaive in generation 8 of 10\n",
            "Model Number: 1083 with model ETS in generation 8 of 10\n",
            "Model Number: 1084 with model Theta in generation 8 of 10\n",
            "Model Number: 1085 with model NVAR in generation 8 of 10\n",
            "Model Number: 1086 with model GLM in generation 8 of 10\n",
            "New Generation: 9 of 10\n",
            "Model Number: 1087 with model ARDL in generation 9 of 10\n",
            "Model Number: 1088 with model UnivariateRegression in generation 9 of 10\n",
            "Model Number: 1089 with model MultivariateRegression in generation 9 of 10\n",
            "Template Eval Error: ValueError('Input X contains NaN.\\nRadiusNeighborsRegressor does not accept missing values encoded as NaN natively. For supervised learning, you might want to consider sklearn.ensemble.HistGradientBoostingClassifier and Regressor which accept missing values encoded as NaNs natively. Alternatively, it is possible to preprocess the data, for instance by using an imputer transformer in a pipeline or drop samples with missing values. See https://scikit-learn.org/stable/modules/impute.html You can find a list of all estimators that handle NaN values at the following page: https://scikit-learn.org/stable/modules/impute.html#estimators-that-handle-nan-values') in model 1089 in generation 9: MultivariateRegression\n",
            "Model Number: 1090 with model DatepartRegression in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_regression.py:494: UserWarning:\n",
            "\n",
            "One or more samples have no neighbors within specified radius; predicting NaN.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_regression.py:494: UserWarning:\n",
            "\n",
            "One or more samples have no neighbors within specified radius; predicting NaN.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 1090 in generation 9: DatepartRegression\n",
            "Model Number: 1091 with model MetricMotif in generation 9 of 10\n",
            "Model Number: 1092 with model UnivariateRegression in generation 9 of 10\n",
            "Model Number: 1093 with model Theta in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1094 with model ConstantNaive in generation 9 of 10\n",
            "Model Number: 1095 with model FBProphet in generation 9 of 10\n",
            "Model Number: 1096 with model Theta in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1097 with model MetricMotif in generation 9 of 10\n",
            "Model Number: 1098 with model Theta in generation 9 of 10\n",
            "Model Number: 1099 with model LastValueNaive in generation 9 of 10\n",
            "Model Number: 1100 with model UnobservedComponents in generation 9 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor supplied\") in model 1100 in generation 9: UnobservedComponents\n",
            "Model Number: 1101 with model ARIMA in generation 9 of 10\n",
            "Model Number: 1102 with model ARIMA in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1103 with model Theta in generation 9 of 10\n",
            "Model Number: 1104 with model DatepartRegression in generation 9 of 10\n",
            "Epoch 1/50\n",
            "22/22 [==============================] - 7s 9ms/step - loss: 1.4393\n",
            "Epoch 2/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4386\n",
            "Epoch 3/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4357\n",
            "Epoch 4/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4330\n",
            "Epoch 5/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4395\n",
            "Epoch 6/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 1.4372\n",
            "Epoch 7/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4366\n",
            "Epoch 8/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4366\n",
            "Epoch 9/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4391\n",
            "Epoch 10/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 1.4366\n",
            "Epoch 11/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4349\n",
            "Epoch 12/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4366\n",
            "Epoch 13/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4388\n",
            "Epoch 14/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4363\n",
            "Epoch 15/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 1.4375\n",
            "Epoch 16/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4373\n",
            "Epoch 17/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4383\n",
            "Epoch 18/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4381\n",
            "Epoch 19/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4377\n",
            "Epoch 20/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4366\n",
            "Epoch 21/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4377\n",
            "Epoch 22/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4373\n",
            "Epoch 23/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4374\n",
            "Epoch 24/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4393\n",
            "Epoch 25/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4360\n",
            "Epoch 26/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 1.4381\n",
            "Epoch 27/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4369\n",
            "Epoch 28/50\n",
            "22/22 [==============================] - 0s 7ms/step - loss: 1.4389\n",
            "Epoch 29/50\n",
            "22/22 [==============================] - 0s 8ms/step - loss: 1.4366\n",
            "Epoch 30/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4373\n",
            "Epoch 31/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 1.4364\n",
            "Epoch 32/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4364\n",
            "Epoch 33/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4376\n",
            "Epoch 34/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4373\n",
            "Epoch 35/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4363\n",
            "Epoch 36/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4373\n",
            "Epoch 37/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4362\n",
            "Epoch 38/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 1.4350\n",
            "Epoch 39/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4388\n",
            "Epoch 40/50\n",
            "22/22 [==============================] - 0s 12ms/step - loss: 1.4377\n",
            "Epoch 41/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 1.4359\n",
            "Epoch 42/50\n",
            "22/22 [==============================] - 0s 14ms/step - loss: 1.4387\n",
            "Epoch 43/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 1.4369\n",
            "Epoch 44/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 1.4376\n",
            "Epoch 45/50\n",
            "22/22 [==============================] - 0s 13ms/step - loss: 1.4354\n",
            "Epoch 46/50\n",
            "22/22 [==============================] - 0s 10ms/step - loss: 1.4364\n",
            "Epoch 47/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4350\n",
            "Epoch 48/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4370\n",
            "Epoch 49/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4363\n",
            "Epoch 50/50\n",
            "22/22 [==============================] - 0s 9ms/step - loss: 1.4352\n",
            "1/1 [==============================] - 2s 2s/step\n",
            "Model Number: 1105 with model FBProphet in generation 9 of 10\n",
            "Model Number: 1106 with model GLS in generation 9 of 10\n",
            "Model Number: 1107 with model MetricMotif in generation 9 of 10\n",
            "Template Eval Error: IndexError('index 593 is out of bounds for axis 0 with size 350') in model 1107 in generation 9: MetricMotif\n",
            "Model Number: 1108 with model NVAR in generation 9 of 10\n",
            "Model Number: 1109 with model FBProphet in generation 9 of 10\n",
            "Model Number: 1110 with model NVAR in generation 9 of 10\n",
            "Model Number: 1111 with model ARDL in generation 9 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but future_regressor not supplied\") in model 1111 in generation 9: ARDL\n",
            "Model Number: 1112 with model Theta in generation 9 of 10\n",
            "Model Number: 1113 with model AverageValueNaive in generation 9 of 10\n",
            "Model Number: 1114 with model GLS in generation 9 of 10\n",
            "Model Number: 1115 with model MultivariateMotif in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer BTCD failed on fit') in model 1115 in generation 9: MultivariateMotif\n",
            "Model Number: 1116 with model UnobservedComponents in generation 9 of 10\n",
            "Model Number: 1117 with model ARIMA in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1118 with model LastValueNaive in generation 9 of 10\n",
            "Model Number: 1119 with model UnobservedComponents in generation 9 of 10\n",
            "Template Eval Error: LinAlgError('Singular matrix') in model 1119 in generation 9: UnobservedComponents\n",
            "Model Number: 1120 with model Theta in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1120 in generation 9: Theta\n",
            "Model Number: 1121 with model DatepartRegression in generation 9 of 10\n",
            "Model Number: 1122 with model ARIMA in generation 9 of 10\n",
            "Model Number: 1123 with model ARIMA in generation 9 of 10\n",
            "Model Number: 1124 with model AverageValueNaive in generation 9 of 10\n",
            "Model Number: 1125 with model ARDL in generation 9 of 10\n",
            "Model Number: 1126 with model UnivariateMotif in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1126 in generation 9: UnivariateMotif\n",
            "Model Number: 1127 with model UnobservedComponents in generation 9 of 10\n",
            "Model Number: 1128 with model ARDL in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1128 in generation 9: ARDL\n",
            "Model Number: 1129 with model MetricMotif in generation 9 of 10\n",
            "Model Number: 1130 with model LastValueNaive in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1131 with model AverageValueNaive in generation 9 of 10\n",
            "Model Number: 1132 with model LastValueNaive in generation 9 of 10\n",
            "Model Number: 1133 with model ETS in generation 9 of 10\n",
            "Model Number: 1134 with model ETS in generation 9 of 10\n",
            "Model Number: 1135 with model GLS in generation 9 of 10\n",
            "Model Number: 1136 with model ARDL in generation 9 of 10\n",
            "Model Number: 1137 with model UnobservedComponents in generation 9 of 10\n",
            "Model Number: 1138 with model Theta in generation 9 of 10\n",
            "Model Number: 1139 with model LastValueNaive in generation 9 of 10\n",
            "Model Number: 1140 with model UnobservedComponents in generation 9 of 10\n",
            "Template Eval Error: ValueError(\"regression_type='User' but no future_regressor supplied\") in model 1140 in generation 9: UnobservedComponents\n",
            "Model Number: 1141 with model ConstantNaive in generation 9 of 10\n",
            "Template Eval Error: ValueError(\"Model returned NaN due to a preprocessing transformer {'fillna': 'ffill', 'transformations': {'0': 'AlignLastValue', '1': 'MinMaxScaler', '2': 'cffilter', '3': 'AlignLastValue'}, 'transformation_params': {'0': {'rows': 1, 'lag': 7, 'method': 'additive', 'strength': 1.0, 'first_value_only': False}, '1': {}, '2': {}, '3': {'rows': 1, 'lag': 1, 'method': 'multiplicative', 'strength': 1.0, 'first_value_only': False}}}. fail_on_forecast_nan=True\") in model 1141 in generation 9: ConstantNaive\n",
            "Model Number: 1142 with model UnobservedComponents in generation 9 of 10\n",
            "Model Number: 1143 with model ARIMA in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1144 with model UnobservedComponents in generation 9 of 10\n",
            "Model Number: 1145 with model GLM in generation 9 of 10\n",
            "Model Number: 1146 with model MultivariateRegression in generation 9 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1147 with model ARDL in generation 9 of 10\n",
            "Model Number: 1148 with model NVAR in generation 9 of 10\n",
            "Model Number: 1149 with model SeasonalNaive in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 1149 in generation 9: SeasonalNaive\n",
            "Model Number: 1150 with model AverageValueNaive in generation 9 of 10\n",
            "Model Number: 1151 with model LastValueNaive in generation 9 of 10\n",
            "Model Number: 1152 with model SectionalMotif in generation 9 of 10\n",
            "Model Number: 1153 with model FBProphet in generation 9 of 10\n",
            "Model Number: 1154 with model MetricMotif in generation 9 of 10\n",
            "Model Number: 1155 with model FBProphet in generation 9 of 10\n",
            "Model Number: 1156 with model SeasonalNaive in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 1156 in generation 9: SeasonalNaive\n",
            "Model Number: 1157 with model Theta in generation 9 of 10\n",
            "Model Number: 1158 with model UnobservedComponents in generation 9 of 10\n",
            "Model Number: 1159 with model SectionalMotif in generation 9 of 10\n",
            "Model Number: 1160 with model ARDL in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1160 in generation 9: ARDL\n",
            "Model Number: 1161 with model SectionalMotif in generation 9 of 10\n",
            "Model Number: 1162 with model SeasonalNaive in generation 9 of 10\n",
            "Model Number: 1163 with model UnivariateMotif in generation 9 of 10\n",
            "Model Number: 1164 with model SeasonalNaive in generation 9 of 10\n",
            "Model Number: 1165 with model UnobservedComponents in generation 9 of 10\n",
            "Model Number: 1166 with model Theta in generation 9 of 10\n",
            "Model Number: 1167 with model GLM in generation 9 of 10\n",
            "Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 1167 in generation 9: GLM\n",
            "Model Number: 1168 with model NVAR in generation 9 of 10\n",
            "Model Number: 1169 with model ConstantNaive in generation 9 of 10\n",
            "Model Number: 1170 with model NVAR in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer MaxAbsScaler failed on inverse') in model 1170 in generation 9: NVAR\n",
            "Model Number: 1171 with model ConstantNaive in generation 9 of 10\n",
            "Model Number: 1172 with model LastValueNaive in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer RegressionFilter failed on fit') in model 1172 in generation 9: LastValueNaive\n",
            "Model Number: 1173 with model GLS in generation 9 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 1173 in generation 9: GLS\n",
            "Model Number: 1174 with model SectionalMotif in generation 9 of 10\n",
            "Template Eval Error: ValueError('Unknown Distance Metric: kulsinski') in model 1174 in generation 9: SectionalMotif\n",
            "Model Number: 1175 with model LastValueNaive in generation 9 of 10\n",
            "Model Number: 1176 with model ARIMA in generation 9 of 10\n",
            "Model Number: 1177 with model SeasonalNaive in generation 9 of 10\n",
            "Model Number: 1178 with model NVAR in generation 9 of 10\n",
            "Model Number: 1179 with model AverageValueNaive in generation 9 of 10\n",
            "Model Number: 1180 with model ARDL in generation 9 of 10\n",
            "Model Number: 1181 with model MultivariateRegression in generation 9 of 10\n",
            "Model Number: 1182 with model ARDL in generation 9 of 10\n",
            "Model Number: 1183 with model Theta in generation 9 of 10\n",
            "Model Number: 1184 with model MultivariateRegression in generation 9 of 10\n",
            "Model Number: 1185 with model MultivariateRegression in generation 9 of 10\n",
            "Model Number: 1186 with model SeasonalNaive in generation 9 of 10\n",
            "New Generation: 10 of 10\n",
            "Model Number: 1187 with model MultivariateRegression in generation 10 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1188 with model ARIMA in generation 10 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_ridge.py:216: LinAlgWarning:\n",
            "\n",
            "Ill-conditioned matrix (rcond=1.52185e-25): result may not be accurate.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1189 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1190 with model UnivariateMotif in generation 10 of 10\n",
            "Model Number: 1191 with model Theta in generation 10 of 10\n",
            "Model Number: 1192 with model AverageValueNaive in generation 10 of 10\n",
            "Model Number: 1193 with model SectionalMotif in generation 10 of 10\n",
            "Model Number: 1194 with model NVAR in generation 10 of 10\n",
            "Model Number: 1195 with model ARDL in generation 10 of 10\n",
            "Model Number: 1196 with model AverageValueNaive in generation 10 of 10\n",
            "Model Number: 1197 with model ARDL in generation 10 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1197 in generation 10: ARDL\n",
            "Model Number: 1198 with model UnobservedComponents in generation 10 of 10\n",
            "Model Number: 1199 with model FBProphet in generation 10 of 10\n",
            "Model Number: 1200 with model ARDL in generation 10 of 10\n",
            "Model Number: 1201 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1202 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1203 with model GLS in generation 10 of 10\n",
            "Model Number: 1204 with model UnobservedComponents in generation 10 of 10\n",
            "Model Number: 1205 with model UnobservedComponents in generation 10 of 10\n",
            "Model Number: 1206 with model AverageValueNaive in generation 10 of 10\n",
            "Model Number: 1207 with model Theta in generation 10 of 10\n",
            "Model Number: 1208 with model AverageValueNaive in generation 10 of 10\n",
            "Model Number: 1209 with model LastValueNaive in generation 10 of 10\n",
            "Model Number: 1210 with model NVAR in generation 10 of 10\n",
            "Model Number: 1211 with model Theta in generation 10 of 10\n",
            "Model Number: 1212 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1213 with model UnobservedComponents in generation 10 of 10\n",
            "Model Number: 1214 with model Theta in generation 10 of 10\n",
            "Model Number: 1215 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1216 with model LastValueNaive in generation 10 of 10\n",
            "Model Number: 1217 with model ARDL in generation 10 of 10\n",
            "Model Number: 1218 with model DatepartRegression in generation 10 of 10\n",
            "Model Number: 1219 with model ARDL in generation 10 of 10\n",
            "Model Number: 1220 with model ARDL in generation 10 of 10\n",
            "Model Number: 1221 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1222 with model LastValueNaive in generation 10 of 10\n",
            "Model Number: 1223 with model MetricMotif in generation 10 of 10\n",
            "Model Number: 1224 with model SectionalMotif in generation 10 of 10\n",
            "Model Number: 1225 with model Theta in generation 10 of 10\n",
            "Model Number: 1226 with model SectionalMotif in generation 10 of 10\n",
            "Model Number: 1227 with model GLS in generation 10 of 10\n",
            "Model Number: 1228 with model GLS in generation 10 of 10\n",
            "Model Number: 1229 with model SectionalMotif in generation 10 of 10\n",
            "Template Eval Error: ValueError(\"regression_type=='User' but no future_regressor supplied\") in model 1229 in generation 10: SectionalMotif\n",
            "Model Number: 1230 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1231 with model SeasonalNaive in generation 10 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:708: FutureWarning:\n",
            "\n",
            "Starting in v1.3, whiten=True should be specified as whiten='arbitrary-variance' (its current behaviour). This behavior is deprecated in 1.1 and will raise ValueError in 1.3.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1232 with model LastValueNaive in generation 10 of 10\n",
            "Model Number: 1233 with model UnobservedComponents in generation 10 of 10\n",
            "Model Number: 1234 with model NVAR in generation 10 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1234 in generation 10: NVAR\n",
            "Model Number: 1235 with model ARIMA in generation 10 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1236 with model FBProphet in generation 10 of 10\n",
            "Model Number: 1237 with model ETS in generation 10 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 1237 in generation 10: ETS\n",
            "Model Number: 1238 with model SectionalMotif in generation 10 of 10\n",
            "Model Number: 1239 with model MetricMotif in generation 10 of 10\n",
            "Model Number: 1240 with model MultivariateRegression in generation 10 of 10\n",
            "Model Number: 1241 with model NVAR in generation 10 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 1241 in generation 10: NVAR\n",
            "Model Number: 1242 with model Theta in generation 10 of 10\n",
            "Model Number: 1243 with model LastValueNaive in generation 10 of 10\n",
            "Model Number: 1244 with model GLS in generation 10 of 10\n",
            "Model Number: 1245 with model MultivariateRegression in generation 10 of 10\n",
            "Model Number: 1246 with model Theta in generation 10 of 10\n",
            "Model Number: 1247 with model MultivariateRegression in generation 10 of 10\n",
            "Model Number: 1248 with model ARDL in generation 10 of 10\n",
            "Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1248 in generation 10: ARDL\n",
            "Model Number: 1249 with model UnobservedComponents in generation 10 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_pca.py:545: RuntimeWarning:\n",
            "\n",
            "invalid value encountered in divide\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1250 with model ARIMA in generation 10 of 10\n",
            "Model Number: 1251 with model NVAR in generation 10 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1252 with model UnivariateMotif in generation 10 of 10\n",
            "Model Number: 1253 with model ETS in generation 10 of 10\n",
            "Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 1253 in generation 10: ETS\n",
            "Model Number: 1254 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1255 with model GLS in generation 10 of 10\n",
            "Model Number: 1256 with model GLS in generation 10 of 10\n",
            "Model Number: 1257 with model ETS in generation 10 of 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning:\n",
            "\n",
            "Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.118e+10, tolerance: 4.391e+06\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1258 with model Theta in generation 10 of 10\n",
            "Model Number: 1259 with model ARIMA in generation 10 of 10\n",
            "Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 1259 in generation 10: ARIMA\n",
            "Model Number: 1260 with model MultivariateRegression in generation 10 of 10\n",
            "Model Number: 1261 with model SeasonalNaive in generation 10 of 10\n",
            "Model Number: 1262 with model Ensemble in generation 11 of Ensembles\n",
            "Model Number: 1263 with model Ensemble in generation 11 of Ensembles\n",
            "Model Number: 1264 with model Ensemble in generation 11 of Ensembles\n",
            "Model Number: 1265 with model Ensemble in generation 11 of Ensembles\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Number: 1266 with model Ensemble in generation 11 of Ensembles\n",
            "Model Number: 1267 with model Ensemble in generation 11 of Ensembles\n",
            "Model Number: 1268 with model Ensemble in generation 11 of Ensembles\n",
            "Model Number: 1269 with model Ensemble in generation 11 of Ensembles\n",
            "Validation Round: 1\n",
            "Model Number: 1 of 191 with model Ensemble for Validation 1\n",
            "📈 1 - Ensemble with avg smape 6.7: \n",
            "Model Number: 2 of 191 with model Ensemble for Validation 1\n",
            "2 - Ensemble with avg smape 8.13: \n",
            "Model Number: 3 of 191 with model Ensemble for Validation 1\n",
            "3 - Ensemble with avg smape 8.13: \n",
            "Model Number: 4 of 191 with model Ensemble for Validation 1\n",
            "4 - Ensemble with avg smape 8.08: \n",
            "Model Number: 5 of 191 with model Ensemble for Validation 1\n",
            "5 - Ensemble with avg smape 6.89: \n",
            "Model Number: 6 of 191 with model UnivariateMotif for Validation 1\n",
            "📈 6 - UnivariateMotif with avg smape 6.5: \n",
            "Model Number: 7 of 191 with model UnivariateMotif for Validation 1\n",
            "7 - UnivariateMotif with avg smape 6.5: \n",
            "Model Number: 8 of 191 with model Ensemble for Validation 1\n",
            "📈 8 - Ensemble with avg smape 6.45: \n",
            "Model Number: 9 of 191 with model SectionalMotif for Validation 1\n",
            "9 - SectionalMotif with avg smape 7.71: \n",
            "Model Number: 10 of 191 with model SectionalMotif for Validation 1\n",
            "10 - SectionalMotif with avg smape 6.63: \n",
            "Model Number: 11 of 191 with model ARDL for Validation 1\n",
            "11 - ARDL with avg smape 10.31: \n",
            "Model Number: 12 of 191 with model ARDL for Validation 1\n",
            "12 - ARDL with avg smape 9.97: \n",
            "Model Number: 13 of 191 with model ARDL for Validation 1\n",
            "13 - ARDL with avg smape 10.95: \n",
            "Model Number: 14 of 191 with model ARDL for Validation 1\n",
            "14 - ARDL with avg smape 10.64: \n",
            "Model Number: 15 of 191 with model ARDL for Validation 1\n",
            "📈 15 - ARDL with avg smape 6.44: \n",
            "Model Number: 16 of 191 with model ARDL for Validation 1\n",
            "16 - ARDL with avg smape 9.76: \n",
            "Model Number: 17 of 191 with model LastValueNaive for Validation 1\n",
            "📈 17 - LastValueNaive with avg smape 5.37: \n",
            "Model Number: 18 of 191 with model LastValueNaive for Validation 1\n",
            "18 - LastValueNaive with avg smape 5.37: \n",
            "Model Number: 19 of 191 with model Theta for Validation 1\n",
            "📈 19 - Theta with avg smape 4.8: \n",
            "Model Number: 20 of 191 with model Theta for Validation 1\n",
            "20 - Theta with avg smape 4.8: \n",
            "Model Number: 21 of 191 with model Theta for Validation 1\n",
            "21 - Theta with avg smape 4.8: \n",
            "Model Number: 22 of 191 with model Theta for Validation 1\n",
            "22 - Theta with avg smape 4.8: \n",
            "Model Number: 23 of 191 with model Theta for Validation 1\n",
            "23 - Theta with avg smape 4.8: \n",
            "Model Number: 24 of 191 with model Theta for Validation 1\n",
            "24 - Theta with avg smape 4.8: \n",
            "Model Number: 25 of 191 with model Theta for Validation 1\n",
            "25 - Theta with avg smape 4.8: \n",
            "Model Number: 26 of 191 with model Theta for Validation 1\n",
            "26 - Theta with avg smape 4.81: \n",
            "Model Number: 27 of 191 with model Theta for Validation 1\n",
            "27 - Theta with avg smape 4.81: \n",
            "Model Number: 28 of 191 with model LastValueNaive for Validation 1\n",
            "28 - LastValueNaive with avg smape 5.27: \n",
            "Model Number: 29 of 191 with model SeasonalNaive for Validation 1\n",
            "📈 29 - SeasonalNaive with avg smape 4.78: \n",
            "Model Number: 30 of 191 with model LastValueNaive for Validation 1\n",
            "📈 30 - LastValueNaive with avg smape 4.72: \n",
            "Model Number: 31 of 191 with model LastValueNaive for Validation 1\n",
            "31 - LastValueNaive with avg smape 4.72: \n",
            "Model Number: 32 of 191 with model NVAR for Validation 1\n",
            "📈 32 - NVAR with avg smape 3.61: \n",
            "Model Number: 33 of 191 with model NVAR for Validation 1\n",
            "33 - NVAR with avg smape 3.61: \n",
            "Model Number: 34 of 191 with model GLS for Validation 1\n",
            "34 - GLS with avg smape 4.58: \n",
            "Model Number: 35 of 191 with model SeasonalNaive for Validation 1\n",
            "35 - SeasonalNaive with avg smape 4.7: \n",
            "Model Number: 36 of 191 with model GLS for Validation 1\n",
            "36 - GLS with avg smape 4.59: \n",
            "Model Number: 37 of 191 with model GLS for Validation 1\n",
            "37 - GLS with avg smape 4.59: \n",
            "Model Number: 38 of 191 with model GLS for Validation 1\n",
            "38 - GLS with avg smape 4.59: \n",
            "Model Number: 39 of 191 with model SeasonalNaive for Validation 1\n",
            "39 - SeasonalNaive with avg smape 4.78: \n",
            "Model Number: 40 of 191 with model SeasonalNaive for Validation 1\n",
            "40 - SeasonalNaive with avg smape 4.78: \n",
            "Model Number: 41 of 191 with model LastValueNaive for Validation 1\n",
            "41 - LastValueNaive with avg smape 9.52: \n",
            "Model Number: 42 of 191 with model SeasonalNaive for Validation 1\n",
            "42 - SeasonalNaive with avg smape 4.72: \n",
            "Model Number: 43 of 191 with model SeasonalNaive for Validation 1\n",
            "43 - SeasonalNaive with avg smape 4.98: \n",
            "Model Number: 44 of 191 with model NVAR for Validation 1\n",
            "44 - NVAR with avg smape 10.3: \n",
            "Model Number: 45 of 191 with model SeasonalNaive for Validation 1\n",
            "45 - SeasonalNaive with avg smape 4.87: \n",
            "Model Number: 46 of 191 with model ARIMA for Validation 1\n",
            "46 - ARIMA with avg smape 6.78: \n",
            "Model Number: 47 of 191 with model LastValueNaive for Validation 1\n",
            "47 - LastValueNaive with avg smape 9.72: \n",
            "Model Number: 48 of 191 with model UnobservedComponents for Validation 1\n",
            "48 - UnobservedComponents with avg smape 4.58: \n",
            "Model Number: 49 of 191 with model UnobservedComponents for Validation 1\n",
            "49 - UnobservedComponents with avg smape 4.58: \n",
            "Model Number: 50 of 191 with model LastValueNaive for Validation 1\n",
            "50 - LastValueNaive with avg smape 9.77: \n",
            "Model Number: 51 of 191 with model LastValueNaive for Validation 1\n",
            "51 - LastValueNaive with avg smape 14.38: \n",
            "Model Number: 52 of 191 with model MultivariateRegression for Validation 1\n",
            "52 - MultivariateRegression with avg smape 6.5: \n",
            "Model Number: 53 of 191 with model MultivariateRegression for Validation 1\n",
            "53 - MultivariateRegression with avg smape 6.66: \n",
            "Model Number: 54 of 191 with model MultivariateRegression for Validation 1\n",
            "54 - MultivariateRegression with avg smape 6.51: \n",
            "Model Number: 55 of 191 with model ARDL for Validation 1\n",
            "55 - ARDL with avg smape 8.58: \n",
            "Model Number: 56 of 191 with model UnobservedComponents for Validation 1\n",
            "56 - UnobservedComponents with avg smape 6.27: \n",
            "Model Number: 57 of 191 with model UnobservedComponents for Validation 1\n",
            "57 - UnobservedComponents with avg smape 6.14: \n",
            "Model Number: 58 of 191 with model UnobservedComponents for Validation 1\n",
            "58 - UnobservedComponents with avg smape 6.13: \n",
            "Model Number: 59 of 191 with model UnobservedComponents for Validation 1\n",
            "59 - UnobservedComponents with avg smape 6.14: \n",
            "Model Number: 60 of 191 with model UnobservedComponents for Validation 1\n",
            "60 - UnobservedComponents with avg smape 6.14: \n",
            "Model Number: 61 of 191 with model ETS for Validation 1\n",
            "61 - ETS with avg smape 5.52: \n",
            "Model Number: 62 of 191 with model ARDL for Validation 1\n",
            "62 - ARDL with avg smape 9.01: \n",
            "Model Number: 63 of 191 with model UnobservedComponents for Validation 1\n",
            "63 - UnobservedComponents with avg smape 6.26: \n",
            "Model Number: 64 of 191 with model UnobservedComponents for Validation 1\n",
            "64 - UnobservedComponents with avg smape 6.26: \n",
            "Model Number: 65 of 191 with model SectionalMotif for Validation 1\n",
            "65 - SectionalMotif with avg smape 8.83: \n",
            "Model Number: 66 of 191 with model FBProphet for Validation 1\n",
            "66 - FBProphet with avg smape 6.09: \n",
            "Model Number: 67 of 191 with model FBProphet for Validation 1\n",
            "67 - FBProphet with avg smape 6.25: \n",
            "Model Number: 68 of 191 with model FBProphet for Validation 1\n",
            "68 - FBProphet with avg smape 6.09: \n",
            "Model Number: 69 of 191 with model AverageValueNaive for Validation 1\n",
            "69 - AverageValueNaive with avg smape 8.54: \n",
            "Model Number: 70 of 191 with model FBProphet for Validation 1\n",
            "70 - FBProphet with avg smape 6.07: \n",
            "Model Number: 71 of 191 with model FBProphet for Validation 1\n",
            "71 - FBProphet with avg smape 6.09: \n",
            "Model Number: 72 of 191 with model GLS for Validation 1\n",
            "72 - GLS with avg smape 6.18: \n",
            "Model Number: 73 of 191 with model FBProphet for Validation 1\n",
            "73 - FBProphet with avg smape 8.59: \n",
            "Model Number: 74 of 191 with model MetricMotif for Validation 1\n",
            "74 - MetricMotif with avg smape 18.12: \n",
            "Model Number: 75 of 191 with model ARDL for Validation 1\n",
            "75 - ARDL with avg smape 7.6: \n",
            "Model Number: 76 of 191 with model SeasonalNaive for Validation 1\n",
            "76 - SeasonalNaive with avg smape 5.84: \n",
            "Model Number: 77 of 191 with model MultivariateRegression for Validation 1\n",
            "77 - MultivariateRegression with avg smape 9.05: \n",
            "Model Number: 78 of 191 with model AverageValueNaive for Validation 1\n",
            "78 - AverageValueNaive with avg smape 4.64: \n",
            "Model Number: 79 of 191 with model MultivariateRegression for Validation 1\n",
            "79 - MultivariateRegression with avg smape 9.03: \n",
            "Model Number: 80 of 191 with model SeasonalNaive for Validation 1\n",
            "80 - SeasonalNaive with avg smape 5.54: \n",
            "Model Number: 81 of 191 with model MultivariateRegression for Validation 1\n",
            "81 - MultivariateRegression with avg smape 8.96: \n",
            "Model Number: 82 of 191 with model NVAR for Validation 1\n",
            "82 - NVAR with avg smape 6.73: \n",
            "Model Number: 83 of 191 with model MetricMotif for Validation 1\n",
            "📈 83 - MetricMotif with avg smape 3.06: \n",
            "Model Number: 84 of 191 with model ARIMA for Validation 1\n",
            "84 - ARIMA with avg smape 5.0: \n",
            "Model Number: 85 of 191 with model ARIMA for Validation 1\n",
            "85 - ARIMA with avg smape 8.22: \n",
            "Model Number: 86 of 191 with model FBProphet for Validation 1\n",
            "86 - FBProphet with avg smape 8.68: \n",
            "Model Number: 87 of 191 with model GLS for Validation 1\n",
            "87 - GLS with avg smape 4.56: \n",
            "Model Number: 88 of 191 with model GLS for Validation 1\n",
            "88 - GLS with avg smape 4.56: \n",
            "Model Number: 89 of 191 with model FBProphet for Validation 1\n",
            "89 - FBProphet with avg smape 8.28: \n",
            "Model Number: 90 of 191 with model FBProphet for Validation 1\n",
            "90 - FBProphet with avg smape 5.94: \n",
            "Model Number: 91 of 191 with model NVAR for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "91 - NVAR with avg smape 3.32: \n",
            "Model Number: 92 of 191 with model AverageValueNaive for Validation 1\n",
            "92 - AverageValueNaive with avg smape 7.75: \n",
            "Model Number: 93 of 191 with model AverageValueNaive for Validation 1\n",
            "93 - AverageValueNaive with avg smape 7.72: \n",
            "Model Number: 94 of 191 with model AverageValueNaive for Validation 1\n",
            "94 - AverageValueNaive with avg smape 7.73: \n",
            "Model Number: 95 of 191 with model AverageValueNaive for Validation 1\n",
            "95 - AverageValueNaive with avg smape 7.73: \n",
            "Model Number: 96 of 191 with model NVAR for Validation 1\n",
            "96 - NVAR with avg smape 13.87: \n",
            "Model Number: 97 of 191 with model DatepartRegression for Validation 1\n",
            "97 - DatepartRegression with avg smape 4.93: \n",
            "Model Number: 98 of 191 with model SectionalMotif for Validation 1\n",
            "98 - SectionalMotif with avg smape 8.82: \n",
            "Model Number: 99 of 191 with model NVAR for Validation 1\n",
            "99 - NVAR with avg smape 16.04: \n",
            "Model Number: 100 of 191 with model UnivariateMotif for Validation 1\n",
            "100 - UnivariateMotif with avg smape 5.27: \n",
            "Model Number: 101 of 191 with model MultivariateRegression for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "101 - MultivariateRegression with avg smape 9.71: \n",
            "Model Number: 102 of 191 with model NVAR for Validation 1\n",
            "102 - NVAR with avg smape 12.62: \n",
            "Model Number: 103 of 191 with model ARIMA for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "103 - ARIMA with avg smape 8.11: \n",
            "Model Number: 104 of 191 with model NVAR for Validation 1\n",
            "104 - NVAR with avg smape 14.3: \n",
            "Model Number: 105 of 191 with model Ensemble for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "105 - Ensemble with avg smape 7.05: \n",
            "Model Number: 106 of 191 with model ARIMA for Validation 1\n",
            "106 - ARIMA with avg smape 8.21: \n",
            "Model Number: 107 of 191 with model ARIMA for Validation 1\n",
            "107 - ARIMA with avg smape 9.37: \n",
            "Model Number: 108 of 191 with model ConstantNaive for Validation 1\n",
            "108 - ConstantNaive with avg smape 7.46: \n",
            "Model Number: 109 of 191 with model ConstantNaive for Validation 1\n",
            "109 - ConstantNaive with avg smape 7.49: \n",
            "Model Number: 110 of 191 with model ConstantNaive for Validation 1\n",
            "110 - ConstantNaive with avg smape 7.49: \n",
            "Model Number: 111 of 191 with model ConstantNaive for Validation 1\n",
            "111 - ConstantNaive with avg smape 7.46: \n",
            "Model Number: 112 of 191 with model ConstantNaive for Validation 1\n",
            "112 - ConstantNaive with avg smape 7.08: \n",
            "Model Number: 113 of 191 with model ConstantNaive for Validation 1\n",
            "113 - ConstantNaive with avg smape 7.08: \n",
            "Model Number: 114 of 191 with model ConstantNaive for Validation 1\n",
            "114 - ConstantNaive with avg smape 7.08: \n",
            "Model Number: 115 of 191 with model ConstantNaive for Validation 1\n",
            "115 - ConstantNaive with avg smape 7.08: \n",
            "Model Number: 116 of 191 with model ConstantNaive for Validation 1\n",
            "116 - ConstantNaive with avg smape 7.08: \n",
            "Model Number: 117 of 191 with model GLS for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:541: ConvergenceWarning:\n",
            "\n",
            "lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "117 - GLS with avg smape 4.58: \n",
            "Model Number: 118 of 191 with model ARIMA for Validation 1\n",
            "118 - ARIMA with avg smape 10.59: \n",
            "Model Number: 119 of 191 with model ARIMA for Validation 1\n",
            "119 - ARIMA with avg smape 10.59: \n",
            "Model Number: 120 of 191 with model MetricMotif for Validation 1\n",
            "120 - MetricMotif with avg smape 15.24: \n",
            "Model Number: 121 of 191 with model AverageValueNaive for Validation 1\n",
            "121 - AverageValueNaive with avg smape 4.62: \n",
            "Model Number: 122 of 191 with model UnivariateMotif for Validation 1\n",
            "122 - UnivariateMotif with avg smape 5.04: \n",
            "Model Number: 123 of 191 with model ETS for Validation 1\n",
            "123 - ETS with avg smape 22.83: \n",
            "Model Number: 124 of 191 with model ARIMA for Validation 1\n",
            "124 - ARIMA with avg smape 5.79: \n",
            "Model Number: 125 of 191 with model UnivariateRegression for Validation 1\n",
            "125 - UnivariateRegression with avg smape 19.05: \n",
            "Model Number: 126 of 191 with model UnivariateRegression for Validation 1\n",
            "126 - UnivariateRegression with avg smape 19.15: \n",
            "Model Number: 127 of 191 with model UnivariateRegression for Validation 1\n",
            "127 - UnivariateRegression with avg smape 19.15: \n",
            "Model Number: 128 of 191 with model UnivariateRegression for Validation 1\n",
            "128 - UnivariateRegression with avg smape 19.15: \n",
            "Model Number: 129 of 191 with model UnivariateRegression for Validation 1\n",
            "129 - UnivariateRegression with avg smape 19.15: \n",
            "Model Number: 130 of 191 with model MetricMotif for Validation 1\n",
            "130 - MetricMotif with avg smape 12.24: \n",
            "Model Number: 131 of 191 with model MetricMotif for Validation 1\n",
            "131 - MetricMotif with avg smape 5.69: \n",
            "Model Number: 132 of 191 with model ETS for Validation 1\n",
            "132 - ETS with avg smape 4.13: \n",
            "Model Number: 133 of 191 with model ETS for Validation 1\n",
            "133 - ETS with avg smape 4.2: \n",
            "Model Number: 134 of 191 with model AverageValueNaive for Validation 1\n",
            "134 - AverageValueNaive with avg smape 9.44: \n",
            "Model Number: 135 of 191 with model AverageValueNaive for Validation 1\n",
            "135 - AverageValueNaive with avg smape 6.25: \n",
            "Model Number: 136 of 191 with model ETS for Validation 1\n",
            "136 - ETS with avg smape 4.11: \n",
            "Model Number: 137 of 191 with model UnivariateRegression for Validation 1\n",
            "137 - UnivariateRegression with avg smape 19.0: \n",
            "Model Number: 138 of 191 with model MultivariateRegression for Validation 1\n",
            "138 - MultivariateRegression with avg smape 9.7: \n",
            "Model Number: 139 of 191 with model DatepartRegression for Validation 1\n",
            "139 - DatepartRegression with avg smape 4.78: \n",
            "Model Number: 140 of 191 with model SectionalMotif for Validation 1\n",
            "140 - SectionalMotif with avg smape 6.42: \n",
            "Model Number: 141 of 191 with model SectionalMotif for Validation 1\n",
            "141 - SectionalMotif with avg smape 6.47: \n",
            "Model Number: 142 of 191 with model UnivariateRegression for Validation 1\n",
            "142 - UnivariateRegression with avg smape 19.37: \n",
            "Model Number: 143 of 191 with model GLM for Validation 1\n",
            "143 - GLM with avg smape 9.38: \n",
            "Model Number: 144 of 191 with model UnivariateRegression for Validation 1\n",
            "144 - UnivariateRegression with avg smape 19.06: \n",
            "Model Number: 145 of 191 with model GLS for Validation 1\n",
            "145 - GLS with avg smape 9.41: \n",
            "Model Number: 146 of 191 with model GLM for Validation 1\n",
            "146 - GLM with avg smape 9.43: \n",
            "Model Number: 147 of 191 with model UnivariateMotif for Validation 1\n",
            "📈 147 - UnivariateMotif with avg smape 2.76: \n",
            "Model Number: 148 of 191 with model ETS for Validation 1\n",
            "148 - ETS with avg smape 26.45: \n",
            "Model Number: 149 of 191 with model ETS for Validation 1\n",
            "149 - ETS with avg smape 4.55: \n",
            "Model Number: 150 of 191 with model UnivariateMotif for Validation 1\n",
            "150 - UnivariateMotif with avg smape 7.22: \n",
            "Model Number: 151 of 191 with model UnivariateRegression for Validation 1\n",
            "151 - UnivariateRegression with avg smape 19.56: \n",
            "Model Number: 152 of 191 with model MetricMotif for Validation 1\n",
            "152 - MetricMotif with avg smape 24.42: \n",
            "Model Number: 153 of 191 with model UnivariateMotif for Validation 1\n",
            "153 - UnivariateMotif with avg smape 26.92: \n",
            "Model Number: 154 of 191 with model MetricMotif for Validation 1\n",
            "154 - MetricMotif with avg smape 7.2: \n",
            "Model Number: 155 of 191 with model MultivariateRegression for Validation 1\n",
            "155 - MultivariateRegression with avg smape 5.28: \n",
            "Model Number: 156 of 191 with model UnivariateMotif for Validation 1\n",
            "156 - UnivariateMotif with avg smape 25.69: \n",
            "Model Number: 157 of 191 with model DatepartRegression for Validation 1\n",
            "157 - DatepartRegression with avg smape 5.73: \n",
            "Model Number: 158 of 191 with model UnivariateMotif for Validation 1\n",
            "158 - UnivariateMotif with avg smape 13.96: \n",
            "Model Number: 159 of 191 with model MetricMotif for Validation 1\n",
            "159 - MetricMotif with avg smape 11.22: \n",
            "Model Number: 160 of 191 with model ETS for Validation 1\n",
            "160 - ETS with avg smape 8.27: \n",
            "Model Number: 161 of 191 with model MetricMotif for Validation 1\n",
            "161 - MetricMotif with avg smape 16.2: \n",
            "Model Number: 162 of 191 with model WindowRegression for Validation 1\n",
            "162 - WindowRegression with avg smape 5.13: \n",
            "Model Number: 163 of 191 with model SectionalMotif for Validation 1\n",
            "163 - SectionalMotif with avg smape 6.45: \n",
            "Model Number: 164 of 191 with model SectionalMotif for Validation 1\n",
            "164 - SectionalMotif with avg smape 6.12: \n",
            "Model Number: 165 of 191 with model ETS for Validation 1\n",
            "165 - ETS with avg smape 9.74: \n",
            "Model Number: 166 of 191 with model DatepartRegression for Validation 1\n",
            "166 - DatepartRegression with avg smape 4.33: \n",
            "Model Number: 167 of 191 with model GLM for Validation 1\n",
            "167 - GLM with avg smape 6.83: \n",
            "Model Number: 168 of 191 with model MultivariateMotif for Validation 1\n",
            "168 - MultivariateMotif with avg smape 8.27: \n",
            "Model Number: 169 of 191 with model MultivariateMotif for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:198: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "169 - MultivariateMotif with avg smape 14.76: \n",
            "Model Number: 170 of 191 with model WindowRegression for Validation 1\n",
            "170 - WindowRegression with avg smape 7.2: \n",
            "Model Number: 171 of 191 with model GLM for Validation 1\n",
            "171 - GLM with avg smape 7.71: \n",
            "Model Number: 172 of 191 with model GLM for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "172 - GLM with avg smape 7.7: \n",
            "Model Number: 173 of 191 with model GLM for Validation 1\n",
            "173 - GLM with avg smape 7.61: \n",
            "Model Number: 174 of 191 with model WindowRegression for Validation 1\n",
            "174 - WindowRegression with avg smape 5.17: \n",
            "Model Number: 175 of 191 with model SectionalMotif for Validation 1\n",
            "175 - SectionalMotif with avg smape 7.63: \n",
            "Model Number: 176 of 191 with model MultivariateMotif for Validation 1\n",
            "176 - MultivariateMotif with avg smape 5.63: \n",
            "Model Number: 177 of 191 with model MultivariateMotif for Validation 1\n",
            "177 - MultivariateMotif with avg smape 15.13: \n",
            "Model Number: 178 of 191 with model WindowRegression for Validation 1\n",
            "178 - WindowRegression with avg smape 19.12: \n",
            "Model Number: 179 of 191 with model WindowRegression for Validation 1\n",
            "179 - WindowRegression with avg smape 18.12: \n",
            "Model Number: 180 of 191 with model DatepartRegression for Validation 1\n",
            "180 - DatepartRegression with avg smape 9.08: \n",
            "Model Number: 181 of 191 with model DatepartRegression for Validation 1\n",
            "181 - DatepartRegression with avg smape 9.08: \n",
            "Model Number: 182 of 191 with model DatepartRegression for Validation 1\n",
            "182 - DatepartRegression with avg smape 9.08: \n",
            "Model Number: 183 of 191 with model DatepartRegression for Validation 1\n",
            "183 - DatepartRegression with avg smape 10.26: \n",
            "Model Number: 184 of 191 with model GLM for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "184 - GLM with avg smape 9.74: \n",
            "Model Number: 185 of 191 with model DatepartRegression for Validation 1\n",
            "185 - DatepartRegression with avg smape 10.87: \n",
            "Model Number: 186 of 191 with model GLM for Validation 1\n",
            "186 - GLM with avg smape 9.74: \n",
            "Model Number: 187 of 191 with model MultivariateMotif for Validation 1\n",
            "187 - MultivariateMotif with avg smape 5.55: \n",
            "Model Number: 188 of 191 with model GLM for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "188 - GLM with avg smape 19.79: \n",
            "Model Number: 189 of 191 with model WindowRegression for Validation 1\n",
            "189 - WindowRegression with avg smape 10.11: \n",
            "Model Number: 190 of 191 with model Ensemble for Validation 1\n",
            "190 - Ensemble with avg smape 24.75: \n",
            "Model Number: 191 of 191 with model MultivariateMotif for Validation 1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "191 - MultivariateMotif with avg smape 5.68: \n",
            "Validation Round: 2\n",
            "Model Number: 1 of 191 with model Ensemble for Validation 2\n",
            "📈 1 - Ensemble with avg smape 15.85: \n",
            "Model Number: 2 of 191 with model Ensemble for Validation 2\n",
            "2 - Ensemble with avg smape 16.26: \n",
            "Model Number: 3 of 191 with model Ensemble for Validation 2\n",
            "3 - Ensemble with avg smape 16.26: \n",
            "Model Number: 4 of 191 with model Ensemble for Validation 2\n",
            "4 - Ensemble with avg smape 16.21: \n",
            "Model Number: 5 of 191 with model Ensemble for Validation 2\n",
            "📈 5 - Ensemble with avg smape 14.76: \n",
            "Model Number: 6 of 191 with model UnivariateMotif for Validation 2\n",
            "📈 6 - UnivariateMotif with avg smape 14.28: \n",
            "Model Number: 7 of 191 with model UnivariateMotif for Validation 2\n",
            "7 - UnivariateMotif with avg smape 14.28: \n",
            "Model Number: 8 of 191 with model Ensemble for Validation 2\n",
            "📈 8 - Ensemble with avg smape 11.12: \n",
            "Model Number: 9 of 191 with model SectionalMotif for Validation 2\n",
            "9 - SectionalMotif with avg smape 15.73: \n",
            "Model Number: 10 of 191 with model SectionalMotif for Validation 2\n",
            "10 - SectionalMotif with avg smape 16.11: \n",
            "Model Number: 11 of 191 with model ARDL for Validation 2\n",
            "11 - ARDL with avg smape 18.85: \n",
            "Model Number: 12 of 191 with model ARDL for Validation 2\n",
            "12 - ARDL with avg smape 18.62: \n",
            "Model Number: 13 of 191 with model ARDL for Validation 2\n",
            "13 - ARDL with avg smape 19.05: \n",
            "Model Number: 14 of 191 with model ARDL for Validation 2\n",
            "14 - ARDL with avg smape 19.18: \n",
            "Model Number: 15 of 191 with model ARDL for Validation 2\n",
            "15 - ARDL with avg smape 21.04: \n",
            "Model Number: 16 of 191 with model ARDL for Validation 2\n",
            "16 - ARDL with avg smape 18.44: \n",
            "Model Number: 17 of 191 with model LastValueNaive for Validation 2\n",
            "📈 17 - LastValueNaive with avg smape 6.66: \n",
            "Model Number: 18 of 191 with model LastValueNaive for Validation 2\n",
            "18 - LastValueNaive with avg smape 6.66: \n",
            "Model Number: 19 of 191 with model Theta for Validation 2\n",
            "19 - Theta with avg smape 6.67: \n",
            "Model Number: 20 of 191 with model Theta for Validation 2\n",
            "20 - Theta with avg smape 6.67: \n",
            "Model Number: 21 of 191 with model Theta for Validation 2\n",
            "21 - Theta with avg smape 6.67: \n",
            "Model Number: 22 of 191 with model Theta for Validation 2\n",
            "22 - Theta with avg smape 6.67: \n",
            "Model Number: 23 of 191 with model Theta for Validation 2\n",
            "23 - Theta with avg smape 6.67: \n",
            "Model Number: 24 of 191 with model Theta for Validation 2\n",
            "24 - Theta with avg smape 6.67: \n",
            "Model Number: 25 of 191 with model Theta for Validation 2\n",
            "25 - Theta with avg smape 6.67: \n",
            "Model Number: 26 of 191 with model Theta for Validation 2\n",
            "26 - Theta with avg smape 6.67: \n",
            "Model Number: 27 of 191 with model Theta for Validation 2\n",
            "27 - Theta with avg smape 6.67: \n",
            "Model Number: 28 of 191 with model LastValueNaive for Validation 2\n",
            "28 - LastValueNaive with avg smape 6.94: \n",
            "Model Number: 29 of 191 with model SeasonalNaive for Validation 2\n",
            "29 - SeasonalNaive with avg smape 6.67: \n",
            "Model Number: 30 of 191 with model LastValueNaive for Validation 2\n",
            "📈 30 - LastValueNaive with avg smape 6.05: \n",
            "Model Number: 31 of 191 with model LastValueNaive for Validation 2\n",
            "31 - LastValueNaive with avg smape 6.05: \n",
            "Model Number: 32 of 191 with model NVAR for Validation 2\n",
            "32 - NVAR with avg smape 19.64: \n",
            "Model Number: 33 of 191 with model NVAR for Validation 2\n",
            "33 - NVAR with avg smape 19.64: \n",
            "Model Number: 34 of 191 with model GLS for Validation 2\n",
            "34 - GLS with avg smape 7.22: \n",
            "Model Number: 35 of 191 with model SeasonalNaive for Validation 2\n",
            "35 - SeasonalNaive with avg smape 6.62: \n",
            "Model Number: 36 of 191 with model GLS for Validation 2\n",
            "36 - GLS with avg smape 7.24: \n",
            "Model Number: 37 of 191 with model GLS for Validation 2\n",
            "37 - GLS with avg smape 7.24: \n",
            "Model Number: 38 of 191 with model GLS for Validation 2\n",
            "38 - GLS with avg smape 7.24: \n",
            "Model Number: 39 of 191 with model SeasonalNaive for Validation 2\n",
            "39 - SeasonalNaive with avg smape 6.62: \n",
            "Model Number: 40 of 191 with model SeasonalNaive for Validation 2\n",
            "40 - SeasonalNaive with avg smape 6.62: \n",
            "Model Number: 41 of 191 with model LastValueNaive for Validation 2\n",
            "41 - LastValueNaive with avg smape 12.87: \n",
            "Model Number: 42 of 191 with model SeasonalNaive for Validation 2\n",
            "42 - SeasonalNaive with avg smape 6.62: \n",
            "Model Number: 43 of 191 with model SeasonalNaive for Validation 2\n",
            "43 - SeasonalNaive with avg smape 6.62: \n",
            "Model Number: 44 of 191 with model NVAR for Validation 2\n",
            "44 - NVAR with avg smape 19.22: \n",
            "Model Number: 45 of 191 with model SeasonalNaive for Validation 2\n",
            "45 - SeasonalNaive with avg smape 6.62: \n",
            "Model Number: 46 of 191 with model ARIMA for Validation 2\n",
            "46 - ARIMA with avg smape 23.87: \n",
            "Model Number: 47 of 191 with model LastValueNaive for Validation 2\n",
            "47 - LastValueNaive with avg smape 12.58: \n",
            "Model Number: 48 of 191 with model UnobservedComponents for Validation 2\n",
            "48 - UnobservedComponents with avg smape 7.9: \n",
            "Model Number: 49 of 191 with model UnobservedComponents for Validation 2\n",
            "49 - UnobservedComponents with avg smape 7.9: \n",
            "Model Number: 50 of 191 with model LastValueNaive for Validation 2\n",
            "50 - LastValueNaive with avg smape 12.58: \n",
            "Model Number: 51 of 191 with model LastValueNaive for Validation 2\n",
            "51 - LastValueNaive with avg smape 13.08: \n",
            "Model Number: 52 of 191 with model MultivariateRegression for Validation 2\n",
            "52 - MultivariateRegression with avg smape 16.58: \n",
            "Model Number: 53 of 191 with model MultivariateRegression for Validation 2\n",
            "53 - MultivariateRegression with avg smape 16.29: \n",
            "Model Number: 54 of 191 with model MultivariateRegression for Validation 2\n",
            "54 - MultivariateRegression with avg smape 16.58: \n",
            "Model Number: 55 of 191 with model ARDL for Validation 2\n",
            "55 - ARDL with avg smape 24.21: \n",
            "Model Number: 56 of 191 with model UnobservedComponents for Validation 2\n",
            "56 - UnobservedComponents with avg smape 6.94: \n",
            "Model Number: 57 of 191 with model UnobservedComponents for Validation 2\n",
            "57 - UnobservedComponents with avg smape 6.58: \n",
            "Model Number: 58 of 191 with model UnobservedComponents for Validation 2\n",
            "58 - UnobservedComponents with avg smape 6.58: \n",
            "Model Number: 59 of 191 with model UnobservedComponents for Validation 2\n",
            "59 - UnobservedComponents with avg smape 6.58: \n",
            "Model Number: 60 of 191 with model UnobservedComponents for Validation 2\n",
            "60 - UnobservedComponents with avg smape 6.58: \n",
            "Model Number: 61 of 191 with model ETS for Validation 2\n",
            "61 - ETS with avg smape 17.42: \n",
            "Model Number: 62 of 191 with model ARDL for Validation 2\n",
            "62 - ARDL with avg smape 24.21: \n",
            "Model Number: 63 of 191 with model UnobservedComponents for Validation 2\n",
            "63 - UnobservedComponents with avg smape 6.6: \n",
            "Model Number: 64 of 191 with model UnobservedComponents for Validation 2\n",
            "64 - UnobservedComponents with avg smape 6.6: \n",
            "Model Number: 65 of 191 with model SectionalMotif for Validation 2\n",
            "65 - SectionalMotif with avg smape 14.78: \n",
            "Model Number: 66 of 191 with model FBProphet for Validation 2\n",
            "66 - FBProphet with avg smape 6.93: \n",
            "Model Number: 67 of 191 with model FBProphet for Validation 2\n",
            "67 - FBProphet with avg smape 6.6: \n",
            "Model Number: 68 of 191 with model FBProphet for Validation 2\n",
            "68 - FBProphet with avg smape 6.93: \n",
            "Model Number: 69 of 191 with model AverageValueNaive for Validation 2\n",
            "69 - AverageValueNaive with avg smape 18.31: \n",
            "Model Number: 70 of 191 with model FBProphet for Validation 2\n",
            "70 - FBProphet with avg smape 6.95: \n",
            "Model Number: 71 of 191 with model FBProphet for Validation 2\n",
            "71 - FBProphet with avg smape 6.93: \n",
            "Model Number: 72 of 191 with model GLS for Validation 2\n",
            "72 - GLS with avg smape 6.28: \n",
            "Model Number: 73 of 191 with model FBProphet for Validation 2\n",
            "73 - FBProphet with avg smape 20.16: \n",
            "Model Number: 74 of 191 with model MetricMotif for Validation 2\n",
            "74 - MetricMotif with avg smape 15.51: \n",
            "Model Number: 75 of 191 with model ARDL for Validation 2\n",
            "75 - ARDL with avg smape 22.47: \n",
            "Model Number: 76 of 191 with model SeasonalNaive for Validation 2\n",
            "76 - SeasonalNaive with avg smape 15.44: \n",
            "Model Number: 77 of 191 with model MultivariateRegression for Validation 2\n",
            "77 - MultivariateRegression with avg smape 18.17: \n",
            "Model Number: 78 of 191 with model AverageValueNaive for Validation 2\n",
            "📈 78 - AverageValueNaive with avg smape 4.93: \n",
            "Model Number: 79 of 191 with model MultivariateRegression for Validation 2\n",
            "79 - MultivariateRegression with avg smape 18.14: \n",
            "Model Number: 80 of 191 with model SeasonalNaive for Validation 2\n",
            "80 - SeasonalNaive with avg smape 6.38: \n",
            "Model Number: 81 of 191 with model MultivariateRegression for Validation 2\n",
            "81 - MultivariateRegression with avg smape 18.92: \n",
            "Model Number: 82 of 191 with model NVAR for Validation 2\n",
            "82 - NVAR with avg smape 16.8: \n",
            "Model Number: 83 of 191 with model MetricMotif for Validation 2\n",
            "83 - MetricMotif with avg smape 19.62: \n",
            "Model Number: 84 of 191 with model ARIMA for Validation 2\n",
            "84 - ARIMA with avg smape 15.23: \n",
            "Model Number: 85 of 191 with model ARIMA for Validation 2\n",
            "85 - ARIMA with avg smape 22.84: \n",
            "Model Number: 86 of 191 with model FBProphet for Validation 2\n",
            "86 - FBProphet with avg smape 19.72: \n",
            "Model Number: 87 of 191 with model GLS for Validation 2\n",
            "📈 87 - GLS with avg smape 4.91: \n",
            "Model Number: 88 of 191 with model GLS for Validation 2\n",
            "88 - GLS with avg smape 4.91: \n",
            "Model Number: 89 of 191 with model FBProphet for Validation 2\n",
            "89 - FBProphet with avg smape 19.62: \n",
            "Model Number: 90 of 191 with model FBProphet for Validation 2\n",
            "90 - FBProphet with avg smape 6.92: \n",
            "Model Number: 91 of 191 with model NVAR for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "91 - NVAR with avg smape 21.53: \n",
            "Model Number: 92 of 191 with model AverageValueNaive for Validation 2\n",
            "92 - AverageValueNaive with avg smape 17.58: \n",
            "Model Number: 93 of 191 with model AverageValueNaive for Validation 2\n",
            "93 - AverageValueNaive with avg smape 17.64: \n",
            "Model Number: 94 of 191 with model AverageValueNaive for Validation 2\n",
            "94 - AverageValueNaive with avg smape 17.64: \n",
            "Model Number: 95 of 191 with model AverageValueNaive for Validation 2\n",
            "95 - AverageValueNaive with avg smape 17.64: \n",
            "Model Number: 96 of 191 with model NVAR for Validation 2\n",
            "96 - NVAR with avg smape 27.56: \n",
            "Model Number: 97 of 191 with model DatepartRegression for Validation 2\n",
            "97 - DatepartRegression with avg smape 5.12: \n",
            "Model Number: 98 of 191 with model SectionalMotif for Validation 2\n",
            "98 - SectionalMotif with avg smape 21.2: \n",
            "Model Number: 99 of 191 with model NVAR for Validation 2\n",
            "99 - NVAR with avg smape 53.0: \n",
            "Model Number: 100 of 191 with model UnivariateMotif for Validation 2\n",
            "100 - UnivariateMotif with avg smape 17.06: \n",
            "Model Number: 101 of 191 with model MultivariateRegression for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "101 - MultivariateRegression with avg smape 19.04: \n",
            "Model Number: 102 of 191 with model NVAR for Validation 2\n",
            "102 - NVAR with avg smape 52.72: \n",
            "Model Number: 103 of 191 with model ARIMA for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "103 - ARIMA with avg smape 24.09: \n",
            "Model Number: 104 of 191 with model NVAR for Validation 2\n",
            "104 - NVAR with avg smape 27.69: \n",
            "Model Number: 105 of 191 with model Ensemble for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "105 - Ensemble with avg smape 16.11: \n",
            "Model Number: 106 of 191 with model ARIMA for Validation 2\n",
            "106 - ARIMA with avg smape 20.29: \n",
            "Model Number: 107 of 191 with model ARIMA for Validation 2\n",
            "107 - ARIMA with avg smape 21.94: \n",
            "Model Number: 108 of 191 with model ConstantNaive for Validation 2\n",
            "108 - ConstantNaive with avg smape 24.83: \n",
            "Model Number: 109 of 191 with model ConstantNaive for Validation 2\n",
            "109 - ConstantNaive with avg smape 24.87: \n",
            "Model Number: 110 of 191 with model ConstantNaive for Validation 2\n",
            "110 - ConstantNaive with avg smape 24.87: \n",
            "Model Number: 111 of 191 with model ConstantNaive for Validation 2\n",
            "111 - ConstantNaive with avg smape 24.83: \n",
            "Model Number: 112 of 191 with model ConstantNaive for Validation 2\n",
            "112 - ConstantNaive with avg smape 24.03: \n",
            "Model Number: 113 of 191 with model ConstantNaive for Validation 2\n",
            "113 - ConstantNaive with avg smape 24.03: \n",
            "Model Number: 114 of 191 with model ConstantNaive for Validation 2\n",
            "114 - ConstantNaive with avg smape 24.03: \n",
            "Model Number: 115 of 191 with model ConstantNaive for Validation 2\n",
            "115 - ConstantNaive with avg smape 24.03: \n",
            "Model Number: 116 of 191 with model ConstantNaive for Validation 2\n",
            "116 - ConstantNaive with avg smape 24.03: \n",
            "Model Number: 117 of 191 with model GLS for Validation 2\n",
            "117 - GLS with avg smape 6.18: \n",
            "Model Number: 118 of 191 with model ARIMA for Validation 2\n",
            "118 - ARIMA with avg smape 20.89: \n",
            "Model Number: 119 of 191 with model ARIMA for Validation 2\n",
            "119 - ARIMA with avg smape 20.88: \n",
            "Model Number: 120 of 191 with model MetricMotif for Validation 2\n",
            "120 - MetricMotif with avg smape 17.23: \n",
            "Model Number: 121 of 191 with model AverageValueNaive for Validation 2\n",
            "📈 121 - AverageValueNaive with avg smape 4.28: \n",
            "Model Number: 122 of 191 with model UnivariateMotif for Validation 2\n",
            "122 - UnivariateMotif with avg smape 19.07: \n",
            "Model Number: 123 of 191 with model ETS for Validation 2\n",
            "123 - ETS with avg smape 28.01: \n",
            "Model Number: 124 of 191 with model ARIMA for Validation 2\n",
            "124 - ARIMA with avg smape 24.0: \n",
            "Model Number: 125 of 191 with model UnivariateRegression for Validation 2\n",
            "125 - UnivariateRegression with avg smape 31.97: \n",
            "Model Number: 126 of 191 with model UnivariateRegression for Validation 2\n",
            "126 - UnivariateRegression with avg smape 32.13: \n",
            "Model Number: 127 of 191 with model UnivariateRegression for Validation 2\n",
            "127 - UnivariateRegression with avg smape 32.13: \n",
            "Model Number: 128 of 191 with model UnivariateRegression for Validation 2\n",
            "128 - UnivariateRegression with avg smape 32.13: \n",
            "Model Number: 129 of 191 with model UnivariateRegression for Validation 2\n",
            "129 - UnivariateRegression with avg smape 32.13: \n",
            "Model Number: 130 of 191 with model MetricMotif for Validation 2\n",
            "130 - MetricMotif with avg smape 13.64: \n",
            "Model Number: 131 of 191 with model MetricMotif for Validation 2\n",
            "131 - MetricMotif with avg smape 14.57: \n",
            "Model Number: 132 of 191 with model ETS for Validation 2\n",
            "132 - ETS with avg smape 19.34: \n",
            "Model Number: 133 of 191 with model ETS for Validation 2\n",
            "133 - ETS with avg smape 19.4: \n",
            "Model Number: 134 of 191 with model AverageValueNaive for Validation 2\n",
            "134 - AverageValueNaive with avg smape 18.88: \n",
            "Model Number: 135 of 191 with model AverageValueNaive for Validation 2\n",
            "135 - AverageValueNaive with avg smape 6.92: \n",
            "Model Number: 136 of 191 with model ETS for Validation 2\n",
            "136 - ETS with avg smape 19.34: \n",
            "Model Number: 137 of 191 with model UnivariateRegression for Validation 2\n",
            "137 - UnivariateRegression with avg smape 26.3: \n",
            "Model Number: 138 of 191 with model MultivariateRegression for Validation 2\n",
            "138 - MultivariateRegression with avg smape 19.04: \n",
            "Model Number: 139 of 191 with model DatepartRegression for Validation 2\n",
            "📈 139 - DatepartRegression with avg smape 3.63: \n",
            "Model Number: 140 of 191 with model SectionalMotif for Validation 2\n",
            "140 - SectionalMotif with avg smape 17.75: \n",
            "Model Number: 141 of 191 with model SectionalMotif for Validation 2\n",
            "141 - SectionalMotif with avg smape 17.56: \n",
            "Model Number: 142 of 191 with model UnivariateRegression for Validation 2\n",
            "142 - UnivariateRegression with avg smape 31.31: \n",
            "Model Number: 143 of 191 with model GLM for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:198: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "143 - GLM with avg smape 18.55: \n",
            "Model Number: 144 of 191 with model UnivariateRegression for Validation 2\n",
            "144 - UnivariateRegression with avg smape 31.85: \n",
            "Model Number: 145 of 191 with model GLS for Validation 2\n",
            "145 - GLS with avg smape 18.86: \n",
            "Model Number: 146 of 191 with model GLM for Validation 2\n",
            "146 - GLM with avg smape 18.87: \n",
            "Model Number: 147 of 191 with model UnivariateMotif for Validation 2\n",
            "147 - UnivariateMotif with avg smape 11.62: \n",
            "Model Number: 148 of 191 with model ETS for Validation 2\n",
            "148 - ETS with avg smape 25.78: \n",
            "Model Number: 149 of 191 with model ETS for Validation 2\n",
            "149 - ETS with avg smape 18.61: \n",
            "Model Number: 150 of 191 with model UnivariateMotif for Validation 2\n",
            "150 - UnivariateMotif with avg smape 15.47: \n",
            "Model Number: 151 of 191 with model UnivariateRegression for Validation 2\n",
            "151 - UnivariateRegression with avg smape 31.22: \n",
            "Model Number: 152 of 191 with model MetricMotif for Validation 2\n",
            "152 - MetricMotif with avg smape 24.06: \n",
            "Model Number: 153 of 191 with model UnivariateMotif for Validation 2\n",
            "153 - UnivariateMotif with avg smape 18.38: \n",
            "Model Number: 154 of 191 with model MetricMotif for Validation 2\n",
            "154 - MetricMotif with avg smape 21.51: \n",
            "Model Number: 155 of 191 with model MultivariateRegression for Validation 2\n",
            "155 - MultivariateRegression with avg smape 14.93: \n",
            "Model Number: 156 of 191 with model UnivariateMotif for Validation 2\n",
            "156 - UnivariateMotif with avg smape 23.27: \n",
            "Model Number: 157 of 191 with model DatepartRegression for Validation 2\n",
            "157 - DatepartRegression with avg smape 4.2: \n",
            "Model Number: 158 of 191 with model UnivariateMotif for Validation 2\n",
            "158 - UnivariateMotif with avg smape 39.15: \n",
            "Model Number: 159 of 191 with model MetricMotif for Validation 2\n",
            "159 - MetricMotif with avg smape 12.89: \n",
            "Model Number: 160 of 191 with model ETS for Validation 2\n",
            "160 - ETS with avg smape 18.03: \n",
            "Model Number: 161 of 191 with model MetricMotif for Validation 2\n",
            "161 - MetricMotif with avg smape 18.6: \n",
            "Model Number: 162 of 191 with model WindowRegression for Validation 2\n",
            "📈 162 - WindowRegression with avg smape 2.52: \n",
            "Model Number: 163 of 191 with model SectionalMotif for Validation 2\n",
            "163 - SectionalMotif with avg smape 17.02: \n",
            "Model Number: 164 of 191 with model SectionalMotif for Validation 2\n",
            "164 - SectionalMotif with avg smape 16.09: \n",
            "Model Number: 165 of 191 with model ETS for Validation 2\n",
            "165 - ETS with avg smape 18.55: \n",
            "Model Number: 166 of 191 with model DatepartRegression for Validation 2\n",
            "166 - DatepartRegression with avg smape 15.09: \n",
            "Model Number: 167 of 191 with model GLM for Validation 2\n",
            "167 - GLM with avg smape 18.97: \n",
            "Model Number: 168 of 191 with model MultivariateMotif for Validation 2\n",
            "168 - MultivariateMotif with avg smape 23.29: \n",
            "Model Number: 169 of 191 with model MultivariateMotif for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:198: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "169 - MultivariateMotif with avg smape 17.92: \n",
            "Model Number: 170 of 191 with model WindowRegression for Validation 2\n",
            "170 - WindowRegression with avg smape 17.65: \n",
            "Model Number: 171 of 191 with model GLM for Validation 2\n",
            "171 - GLM with avg smape 18.39: \n",
            "Model Number: 172 of 191 with model GLM for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "172 - GLM with avg smape 18.37: \n",
            "Model Number: 173 of 191 with model GLM for Validation 2\n",
            "173 - GLM with avg smape 18.39: \n",
            "Model Number: 174 of 191 with model WindowRegression for Validation 2\n",
            "174 - WindowRegression with avg smape 3.99: \n",
            "Model Number: 175 of 191 with model SectionalMotif for Validation 2\n",
            "175 - SectionalMotif with avg smape 17.84: \n",
            "Model Number: 176 of 191 with model MultivariateMotif for Validation 2\n",
            "176 - MultivariateMotif with avg smape 12.8: \n",
            "Model Number: 177 of 191 with model MultivariateMotif for Validation 2\n",
            "177 - MultivariateMotif with avg smape 22.93: \n",
            "Model Number: 178 of 191 with model WindowRegression for Validation 2\n",
            "178 - WindowRegression with avg smape 20.35: \n",
            "Model Number: 179 of 191 with model WindowRegression for Validation 2\n",
            "179 - WindowRegression with avg smape 19.74: \n",
            "Model Number: 180 of 191 with model DatepartRegression for Validation 2\n",
            "180 - DatepartRegression with avg smape 22.0: \n",
            "Model Number: 181 of 191 with model DatepartRegression for Validation 2\n",
            "181 - DatepartRegression with avg smape 22.0: \n",
            "Model Number: 182 of 191 with model DatepartRegression for Validation 2\n",
            "182 - DatepartRegression with avg smape 22.0: \n",
            "Model Number: 183 of 191 with model DatepartRegression for Validation 2\n",
            "183 - DatepartRegression with avg smape 19.33: \n",
            "Model Number: 184 of 191 with model GLM for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "184 - GLM with avg smape 18.55: \n",
            "Model Number: 185 of 191 with model DatepartRegression for Validation 2\n",
            "185 - DatepartRegression with avg smape 20.0: \n",
            "Model Number: 186 of 191 with model GLM for Validation 2\n",
            "186 - GLM with avg smape 18.55: \n",
            "Model Number: 187 of 191 with model MultivariateMotif for Validation 2\n",
            "187 - MultivariateMotif with avg smape 12.97: \n",
            "Model Number: 188 of 191 with model GLM for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "188 - GLM with avg smape 28.37: \n",
            "Model Number: 189 of 191 with model WindowRegression for Validation 2\n",
            "189 - WindowRegression with avg smape 20.08: \n",
            "Model Number: 190 of 191 with model Ensemble for Validation 2\n",
            "190 - Ensemble with avg smape 17.27: \n",
            "Model Number: 191 of 191 with model MultivariateMotif for Validation 2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "191 - MultivariateMotif with avg smape 15.01: \n",
            "Validation Round: 3\n",
            "Model Number: 1 of 191 with model Ensemble for Validation 3\n",
            "📈 1 - Ensemble with avg smape 3.73: \n",
            "Model Number: 2 of 191 with model Ensemble for Validation 3\n",
            "📈 2 - Ensemble with avg smape 2.76: \n",
            "Model Number: 3 of 191 with model Ensemble for Validation 3\n",
            "3 - Ensemble with avg smape 2.76: \n",
            "Model Number: 4 of 191 with model Ensemble for Validation 3\n",
            "4 - Ensemble with avg smape 2.84: \n",
            "Model Number: 5 of 191 with model Ensemble for Validation 3\n",
            "5 - Ensemble with avg smape 4.08: \n",
            "Model Number: 6 of 191 with model UnivariateMotif for Validation 3\n",
            "6 - UnivariateMotif with avg smape 3.73: \n",
            "Model Number: 7 of 191 with model UnivariateMotif for Validation 3\n",
            "7 - UnivariateMotif with avg smape 3.73: \n",
            "Model Number: 8 of 191 with model Ensemble for Validation 3\n",
            "8 - Ensemble with avg smape 9.23: \n",
            "Model Number: 9 of 191 with model SectionalMotif for Validation 3\n",
            "9 - SectionalMotif with avg smape 4.77: \n",
            "Model Number: 10 of 191 with model SectionalMotif for Validation 3\n",
            "10 - SectionalMotif with avg smape 3.86: \n",
            "Model Number: 11 of 191 with model ARDL for Validation 3\n",
            "📈 11 - ARDL with avg smape 1.93: \n",
            "Model Number: 12 of 191 with model ARDL for Validation 3\n",
            "📈 12 - ARDL with avg smape 1.85: \n",
            "Model Number: 13 of 191 with model ARDL for Validation 3\n",
            "13 - ARDL with avg smape 2.5: \n",
            "Model Number: 14 of 191 with model ARDL for Validation 3\n",
            "14 - ARDL with avg smape 2.39: \n",
            "Model Number: 15 of 191 with model ARDL for Validation 3\n",
            "15 - ARDL with avg smape 5.1: \n",
            "Model Number: 16 of 191 with model ARDL for Validation 3\n",
            "📈 16 - ARDL with avg smape 1.8: \n",
            "Model Number: 17 of 191 with model LastValueNaive for Validation 3\n",
            "17 - LastValueNaive with avg smape 14.41: \n",
            "Model Number: 18 of 191 with model LastValueNaive for Validation 3\n",
            "18 - LastValueNaive with avg smape 14.41: \n",
            "Model Number: 19 of 191 with model Theta for Validation 3\n",
            "19 - Theta with avg smape 16.1: \n",
            "Model Number: 20 of 191 with model Theta for Validation 3\n",
            "20 - Theta with avg smape 16.1: \n",
            "Model Number: 21 of 191 with model Theta for Validation 3\n",
            "21 - Theta with avg smape 16.1: \n",
            "Model Number: 22 of 191 with model Theta for Validation 3\n",
            "22 - Theta with avg smape 16.1: \n",
            "Model Number: 23 of 191 with model Theta for Validation 3\n",
            "23 - Theta with avg smape 16.02: \n",
            "Model Number: 24 of 191 with model Theta for Validation 3\n",
            "24 - Theta with avg smape 16.1: \n",
            "Model Number: 25 of 191 with model Theta for Validation 3\n",
            "25 - Theta with avg smape 16.02: \n",
            "Model Number: 26 of 191 with model Theta for Validation 3\n",
            "26 - Theta with avg smape 16.1: \n",
            "Model Number: 27 of 191 with model Theta for Validation 3\n",
            "27 - Theta with avg smape 16.1: \n",
            "Model Number: 28 of 191 with model LastValueNaive for Validation 3\n",
            "28 - LastValueNaive with avg smape 14.74: \n",
            "Model Number: 29 of 191 with model SeasonalNaive for Validation 3\n",
            "29 - SeasonalNaive with avg smape 16.05: \n",
            "Model Number: 30 of 191 with model LastValueNaive for Validation 3\n",
            "30 - LastValueNaive with avg smape 16.41: \n",
            "Model Number: 31 of 191 with model LastValueNaive for Validation 3\n",
            "31 - LastValueNaive with avg smape 16.41: \n",
            "Model Number: 32 of 191 with model NVAR for Validation 3\n",
            "32 - NVAR with avg smape 6.32: \n",
            "Model Number: 33 of 191 with model NVAR for Validation 3\n",
            "33 - NVAR with avg smape 6.32: \n",
            "Model Number: 34 of 191 with model GLS for Validation 3\n",
            "34 - GLS with avg smape 16.29: \n",
            "Model Number: 35 of 191 with model SeasonalNaive for Validation 3\n",
            "35 - SeasonalNaive with avg smape 16.31: \n",
            "Model Number: 36 of 191 with model GLS for Validation 3\n",
            "36 - GLS with avg smape 16.28: \n",
            "Model Number: 37 of 191 with model GLS for Validation 3\n",
            "37 - GLS with avg smape 16.28: \n",
            "Model Number: 38 of 191 with model GLS for Validation 3\n",
            "38 - GLS with avg smape 16.28: \n",
            "Model Number: 39 of 191 with model SeasonalNaive for Validation 3\n",
            "39 - SeasonalNaive with avg smape 16.02: \n",
            "Model Number: 40 of 191 with model SeasonalNaive for Validation 3\n",
            "40 - SeasonalNaive with avg smape 16.02: \n",
            "Model Number: 41 of 191 with model LastValueNaive for Validation 3\n",
            "41 - LastValueNaive with avg smape 3.64: \n",
            "Model Number: 42 of 191 with model SeasonalNaive for Validation 3\n",
            "42 - SeasonalNaive with avg smape 16.16: \n",
            "Model Number: 43 of 191 with model SeasonalNaive for Validation 3\n",
            "43 - SeasonalNaive with avg smape 15.74: \n",
            "Model Number: 44 of 191 with model NVAR for Validation 3\n",
            "44 - NVAR with avg smape 1.8: \n",
            "Model Number: 45 of 191 with model SeasonalNaive for Validation 3\n",
            "45 - SeasonalNaive with avg smape 15.88: \n",
            "Model Number: 46 of 191 with model ARIMA for Validation 3\n",
            "46 - ARIMA with avg smape 7.82: \n",
            "Model Number: 47 of 191 with model LastValueNaive for Validation 3\n",
            "47 - LastValueNaive with avg smape 3.93: \n",
            "Model Number: 48 of 191 with model UnobservedComponents for Validation 3\n",
            "48 - UnobservedComponents with avg smape 15.42: \n",
            "Model Number: 49 of 191 with model UnobservedComponents for Validation 3\n",
            "49 - UnobservedComponents with avg smape 15.42: \n",
            "Model Number: 50 of 191 with model LastValueNaive for Validation 3\n",
            "50 - LastValueNaive with avg smape 3.93: \n",
            "Model Number: 51 of 191 with model LastValueNaive for Validation 3\n",
            "51 - LastValueNaive with avg smape 4.47: \n",
            "Model Number: 52 of 191 with model MultivariateRegression for Validation 3\n",
            "52 - MultivariateRegression with avg smape 3.21: \n",
            "Model Number: 53 of 191 with model MultivariateRegression for Validation 3\n",
            "53 - MultivariateRegression with avg smape 3.34: \n",
            "Model Number: 54 of 191 with model MultivariateRegression for Validation 3\n",
            "54 - MultivariateRegression with avg smape 3.23: \n",
            "Model Number: 55 of 191 with model ARDL for Validation 3\n",
            "55 - ARDL with avg smape 7.67: \n",
            "Model Number: 56 of 191 with model UnobservedComponents for Validation 3\n",
            "56 - UnobservedComponents with avg smape 13.9: \n",
            "Model Number: 57 of 191 with model UnobservedComponents for Validation 3\n",
            "57 - UnobservedComponents with avg smape 14.34: \n",
            "Model Number: 58 of 191 with model UnobservedComponents for Validation 3\n",
            "58 - UnobservedComponents with avg smape 14.34: \n",
            "Model Number: 59 of 191 with model UnobservedComponents for Validation 3\n",
            "59 - UnobservedComponents with avg smape 14.34: \n",
            "Model Number: 60 of 191 with model UnobservedComponents for Validation 3\n",
            "60 - UnobservedComponents with avg smape 14.34: \n",
            "Model Number: 61 of 191 with model ETS for Validation 3\n",
            "61 - ETS with avg smape 3.14: \n",
            "Model Number: 62 of 191 with model ARDL for Validation 3\n",
            "62 - ARDL with avg smape 7.68: \n",
            "Model Number: 63 of 191 with model UnobservedComponents for Validation 3\n",
            "63 - UnobservedComponents with avg smape 14.32: \n",
            "Model Number: 64 of 191 with model UnobservedComponents for Validation 3\n",
            "64 - UnobservedComponents with avg smape 14.32: \n",
            "Model Number: 65 of 191 with model SectionalMotif for Validation 3\n",
            "65 - SectionalMotif with avg smape 4.19: \n",
            "Model Number: 66 of 191 with model FBProphet for Validation 3\n",
            "66 - FBProphet with avg smape 14.41: \n",
            "Model Number: 67 of 191 with model FBProphet for Validation 3\n",
            "67 - FBProphet with avg smape 14.31: \n",
            "Model Number: 68 of 191 with model FBProphet for Validation 3\n",
            "68 - FBProphet with avg smape 14.41: \n",
            "Model Number: 69 of 191 with model AverageValueNaive for Validation 3\n",
            "69 - AverageValueNaive with avg smape 2.7: \n",
            "Model Number: 70 of 191 with model FBProphet for Validation 3\n",
            "70 - FBProphet with avg smape 14.39: \n",
            "Model Number: 71 of 191 with model FBProphet for Validation 3\n",
            "71 - FBProphet with avg smape 14.38: \n",
            "Model Number: 72 of 191 with model GLS for Validation 3\n",
            "72 - GLS with avg smape 14.69: \n",
            "Model Number: 73 of 191 with model FBProphet for Validation 3\n",
            "73 - FBProphet with avg smape 2.96: \n",
            "Model Number: 74 of 191 with model MetricMotif for Validation 3\n",
            "74 - MetricMotif with avg smape 4.52: \n",
            "Model Number: 75 of 191 with model ARDL for Validation 3\n",
            "75 - ARDL with avg smape 6.23: \n",
            "Model Number: 76 of 191 with model SeasonalNaive for Validation 3\n",
            "📈 76 - SeasonalNaive with avg smape 1.69: \n",
            "Model Number: 77 of 191 with model MultivariateRegression for Validation 3\n",
            "77 - MultivariateRegression with avg smape 3.04: \n",
            "Model Number: 78 of 191 with model AverageValueNaive for Validation 3\n",
            "78 - AverageValueNaive with avg smape 17.76: \n",
            "Model Number: 79 of 191 with model MultivariateRegression for Validation 3\n",
            "79 - MultivariateRegression with avg smape 3.05: \n",
            "Model Number: 80 of 191 with model SeasonalNaive for Validation 3\n",
            "80 - SeasonalNaive with avg smape 14.57: \n",
            "Model Number: 81 of 191 with model MultivariateRegression for Validation 3\n",
            "81 - MultivariateRegression with avg smape 3.04: \n",
            "Model Number: 82 of 191 with model NVAR for Validation 3\n",
            "82 - NVAR with avg smape 3.23: \n",
            "Model Number: 83 of 191 with model MetricMotif for Validation 3\n",
            "83 - MetricMotif with avg smape 2.96: \n",
            "Model Number: 84 of 191 with model ARIMA for Validation 3\n",
            "84 - ARIMA with avg smape 1.86: \n",
            "Model Number: 85 of 191 with model ARIMA for Validation 3\n",
            "85 - ARIMA with avg smape 4.05: \n",
            "Model Number: 86 of 191 with model FBProphet for Validation 3\n",
            "86 - FBProphet with avg smape 2.97: \n",
            "Model Number: 87 of 191 with model GLS for Validation 3\n",
            "87 - GLS with avg smape 17.7: \n",
            "Model Number: 88 of 191 with model GLS for Validation 3\n",
            "88 - GLS with avg smape 17.7: \n",
            "Model Number: 89 of 191 with model FBProphet for Validation 3\n",
            "89 - FBProphet with avg smape 3.03: \n",
            "Model Number: 90 of 191 with model FBProphet for Validation 3\n",
            "90 - FBProphet with avg smape 14.25: \n",
            "Model Number: 91 of 191 with model NVAR for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "91 - NVAR with avg smape 7.03: \n",
            "Model Number: 92 of 191 with model AverageValueNaive for Validation 3\n",
            "92 - AverageValueNaive with avg smape 2.08: \n",
            "Model Number: 93 of 191 with model AverageValueNaive for Validation 3\n",
            "93 - AverageValueNaive with avg smape 2.1: \n",
            "Model Number: 94 of 191 with model AverageValueNaive for Validation 3\n",
            "94 - AverageValueNaive with avg smape 2.1: \n",
            "Model Number: 95 of 191 with model AverageValueNaive for Validation 3\n",
            "95 - AverageValueNaive with avg smape 2.1: \n",
            "Model Number: 96 of 191 with model NVAR for Validation 3\n",
            "96 - NVAR with avg smape 5.93: \n",
            "Model Number: 97 of 191 with model DatepartRegression for Validation 3\n",
            "97 - DatepartRegression with avg smape 17.21: \n",
            "Model Number: 98 of 191 with model SectionalMotif for Validation 3\n",
            "98 - SectionalMotif with avg smape 3.33: \n",
            "Model Number: 99 of 191 with model NVAR for Validation 3\n",
            "99 - NVAR with avg smape 55.3: \n",
            "Model Number: 100 of 191 with model UnivariateMotif for Validation 3\n",
            "100 - UnivariateMotif with avg smape 1.84: \n",
            "Model Number: 101 of 191 with model MultivariateRegression for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "101 - MultivariateRegression with avg smape 3.48: \n",
            "Model Number: 102 of 191 with model NVAR for Validation 3\n",
            "102 - NVAR with avg smape 51.16: \n",
            "Model Number: 103 of 191 with model ARIMA for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning:\n",
            "\n",
            "A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "103 - ARIMA with avg smape 4.05: \n",
            "Model Number: 104 of 191 with model NVAR for Validation 3\n",
            "104 - NVAR with avg smape 6.07: \n",
            "Model Number: 105 of 191 with model Ensemble for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "105 - Ensemble with avg smape 3.91: \n",
            "Model Number: 106 of 191 with model ARIMA for Validation 3\n",
            "106 - ARIMA with avg smape 4.89: \n",
            "Model Number: 107 of 191 with model ARIMA for Validation 3\n",
            "107 - ARIMA with avg smape 4.93: \n",
            "Model Number: 108 of 191 with model ConstantNaive for Validation 3\n",
            "108 - ConstantNaive with avg smape 8.68: \n",
            "Model Number: 109 of 191 with model ConstantNaive for Validation 3\n",
            "109 - ConstantNaive with avg smape 8.72: \n",
            "Model Number: 110 of 191 with model ConstantNaive for Validation 3\n",
            "110 - ConstantNaive with avg smape 8.72: \n",
            "Model Number: 111 of 191 with model ConstantNaive for Validation 3\n",
            "111 - ConstantNaive with avg smape 8.68: \n",
            "Model Number: 112 of 191 with model ConstantNaive for Validation 3\n",
            "112 - ConstantNaive with avg smape 7.67: \n",
            "Model Number: 113 of 191 with model ConstantNaive for Validation 3\n",
            "113 - ConstantNaive with avg smape 7.67: \n",
            "Model Number: 114 of 191 with model ConstantNaive for Validation 3\n",
            "114 - ConstantNaive with avg smape 7.67: \n",
            "Model Number: 115 of 191 with model ConstantNaive for Validation 3\n",
            "115 - ConstantNaive with avg smape 7.67: \n",
            "Model Number: 116 of 191 with model ConstantNaive for Validation 3\n",
            "116 - ConstantNaive with avg smape 7.67: \n",
            "Model Number: 117 of 191 with model GLS for Validation 3\n",
            "117 - GLS with avg smape 14.69: \n",
            "Model Number: 118 of 191 with model ARIMA for Validation 3\n",
            "118 - ARIMA with avg smape 4.2: \n",
            "Model Number: 119 of 191 with model ARIMA for Validation 3\n",
            "119 - ARIMA with avg smape 4.2: \n",
            "Model Number: 120 of 191 with model MetricMotif for Validation 3\n",
            "120 - MetricMotif with avg smape 4.56: \n",
            "Model Number: 121 of 191 with model AverageValueNaive for Validation 3\n",
            "121 - AverageValueNaive with avg smape 18.64: \n",
            "Model Number: 122 of 191 with model UnivariateMotif for Validation 3\n",
            "122 - UnivariateMotif with avg smape 2.75: \n",
            "Model Number: 123 of 191 with model ETS for Validation 3\n",
            "123 - ETS with avg smape 3.38: \n",
            "Model Number: 124 of 191 with model ARIMA for Validation 3\n",
            "124 - ARIMA with avg smape 8.2: \n",
            "Model Number: 125 of 191 with model UnivariateRegression for Validation 3\n",
            "125 - UnivariateRegression with avg smape 4.54: \n",
            "Model Number: 126 of 191 with model UnivariateRegression for Validation 3\n",
            "126 - UnivariateRegression with avg smape 4.43: \n",
            "Model Number: 127 of 191 with model UnivariateRegression for Validation 3\n",
            "127 - UnivariateRegression with avg smape 4.43: \n",
            "Model Number: 128 of 191 with model UnivariateRegression for Validation 3\n",
            "128 - UnivariateRegression with avg smape 4.43: \n",
            "Model Number: 129 of 191 with model UnivariateRegression for Validation 3\n",
            "129 - UnivariateRegression with avg smape 4.43: \n",
            "Model Number: 130 of 191 with model MetricMotif for Validation 3\n",
            "130 - MetricMotif with avg smape 5.4: \n",
            "Model Number: 131 of 191 with model MetricMotif for Validation 3\n",
            "131 - MetricMotif with avg smape 5.97: \n",
            "Model Number: 132 of 191 with model ETS for Validation 3\n",
            "132 - ETS with avg smape 4.1: \n",
            "Model Number: 133 of 191 with model ETS for Validation 3\n",
            "133 - ETS with avg smape 4.21: \n",
            "Model Number: 134 of 191 with model AverageValueNaive for Validation 3\n",
            "134 - AverageValueNaive with avg smape 3.08: \n",
            "Model Number: 135 of 191 with model AverageValueNaive for Validation 3\n",
            "135 - AverageValueNaive with avg smape 13.89: \n",
            "Model Number: 136 of 191 with model ETS for Validation 3\n",
            "136 - ETS with avg smape 4.11: \n",
            "Model Number: 137 of 191 with model UnivariateRegression for Validation 3\n",
            "137 - UnivariateRegression with avg smape 6.58: \n",
            "Model Number: 138 of 191 with model MultivariateRegression for Validation 3\n",
            "138 - MultivariateRegression with avg smape 3.49: \n",
            "Model Number: 139 of 191 with model DatepartRegression for Validation 3\n",
            "139 - DatepartRegression with avg smape 19.47: \n",
            "Model Number: 140 of 191 with model SectionalMotif for Validation 3\n",
            "140 - SectionalMotif with avg smape 3.32: \n",
            "Model Number: 141 of 191 with model SectionalMotif for Validation 3\n",
            "📈 141 - SectionalMotif with avg smape 1.65: \n",
            "Model Number: 142 of 191 with model UnivariateRegression for Validation 3\n",
            "142 - UnivariateRegression with avg smape 3.5: \n",
            "Model Number: 143 of 191 with model GLM for Validation 3\n",
            "143 - GLM with avg smape 2.62: \n",
            "Model Number: 144 of 191 with model UnivariateRegression for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:198: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "144 - UnivariateRegression with avg smape 4.31: \n",
            "Model Number: 145 of 191 with model GLS for Validation 3\n",
            "145 - GLS with avg smape 3.07: \n",
            "Model Number: 146 of 191 with model GLM for Validation 3\n",
            "146 - GLM with avg smape 3.09: \n",
            "Model Number: 147 of 191 with model UnivariateMotif for Validation 3\n",
            "147 - UnivariateMotif with avg smape 1.76: \n",
            "Model Number: 148 of 191 with model ETS for Validation 3\n",
            "148 - ETS with avg smape 4.08: \n",
            "Model Number: 149 of 191 with model ETS for Validation 3\n",
            "149 - ETS with avg smape 3.0: \n",
            "Model Number: 150 of 191 with model UnivariateMotif for Validation 3\n",
            "150 - UnivariateMotif with avg smape 2.43: \n",
            "Model Number: 151 of 191 with model UnivariateRegression for Validation 3\n",
            "151 - UnivariateRegression with avg smape 3.97: \n",
            "Model Number: 152 of 191 with model MetricMotif for Validation 3\n",
            "152 - MetricMotif with avg smape 4.87: \n",
            "Model Number: 153 of 191 with model UnivariateMotif for Validation 3\n",
            "153 - UnivariateMotif with avg smape 5.35: \n",
            "Model Number: 154 of 191 with model MetricMotif for Validation 3\n",
            "154 - MetricMotif with avg smape 5.18: \n",
            "Model Number: 155 of 191 with model MultivariateRegression for Validation 3\n",
            "155 - MultivariateRegression with avg smape 3.54: \n",
            "Model Number: 156 of 191 with model UnivariateMotif for Validation 3\n",
            "156 - UnivariateMotif with avg smape 4.53: \n",
            "Model Number: 157 of 191 with model DatepartRegression for Validation 3\n",
            "157 - DatepartRegression with avg smape 19.13: \n",
            "Model Number: 158 of 191 with model UnivariateMotif for Validation 3\n",
            "158 - UnivariateMotif with avg smape 27.06: \n",
            "Model Number: 159 of 191 with model MetricMotif for Validation 3\n",
            "159 - MetricMotif with avg smape 6.72: \n",
            "Model Number: 160 of 191 with model ETS for Validation 3\n",
            "160 - ETS with avg smape 3.58: \n",
            "Model Number: 161 of 191 with model MetricMotif for Validation 3\n",
            "161 - MetricMotif with avg smape 2.76: \n",
            "Model Number: 162 of 191 with model WindowRegression for Validation 3\n",
            "162 - WindowRegression with avg smape 19.93: \n",
            "Model Number: 163 of 191 with model SectionalMotif for Validation 3\n",
            "163 - SectionalMotif with avg smape 3.23: \n",
            "Model Number: 164 of 191 with model SectionalMotif for Validation 3\n",
            "164 - SectionalMotif with avg smape 4.07: \n",
            "Model Number: 165 of 191 with model ETS for Validation 3\n",
            "165 - ETS with avg smape 2.62: \n",
            "Model Number: 166 of 191 with model DatepartRegression for Validation 3\n",
            "166 - DatepartRegression with avg smape 1.71: \n",
            "Model Number: 167 of 191 with model GLM for Validation 3\n",
            "167 - GLM with avg smape 2.55: \n",
            "Model Number: 168 of 191 with model MultivariateMotif for Validation 3\n",
            "168 - MultivariateMotif with avg smape 2.21: \n",
            "Model Number: 169 of 191 with model MultivariateMotif for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/links.py:198: RuntimeWarning:\n",
            "\n",
            "overflow encountered in exp\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "169 - MultivariateMotif with avg smape 1.8: \n",
            "Model Number: 170 of 191 with model WindowRegression for Validation 3\n",
            "170 - WindowRegression with avg smape 1.98: \n",
            "Model Number: 171 of 191 with model GLM for Validation 3\n",
            "171 - GLM with avg smape 2.58: \n",
            "Model Number: 172 of 191 with model GLM for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "172 - GLM with avg smape 2.57: \n",
            "Model Number: 173 of 191 with model GLM for Validation 3\n",
            "173 - GLM with avg smape 2.57: \n",
            "Model Number: 174 of 191 with model WindowRegression for Validation 3\n",
            "174 - WindowRegression with avg smape 21.44: \n",
            "Model Number: 175 of 191 with model SectionalMotif for Validation 3\n",
            "175 - SectionalMotif with avg smape 2.57: \n",
            "Model Number: 176 of 191 with model MultivariateMotif for Validation 3\n",
            "176 - MultivariateMotif with avg smape 8.81: \n",
            "Model Number: 177 of 191 with model MultivariateMotif for Validation 3\n",
            "177 - MultivariateMotif with avg smape 15.93: \n",
            "Model Number: 178 of 191 with model WindowRegression for Validation 3\n",
            "178 - WindowRegression with avg smape 11.79: \n",
            "Model Number: 179 of 191 with model WindowRegression for Validation 3\n",
            "179 - WindowRegression with avg smape 3.26: \n",
            "Model Number: 180 of 191 with model DatepartRegression for Validation 3\n",
            "180 - DatepartRegression with avg smape 30.25: \n",
            "Model Number: 181 of 191 with model DatepartRegression for Validation 3\n",
            "181 - DatepartRegression with avg smape 30.25: \n",
            "Model Number: 182 of 191 with model DatepartRegression for Validation 3\n",
            "182 - DatepartRegression with avg smape 30.25: \n",
            "Model Number: 183 of 191 with model DatepartRegression for Validation 3\n",
            "183 - DatepartRegression with avg smape 3.51: \n",
            "Model Number: 184 of 191 with model GLM for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning:\n",
            "\n",
            "Liblinear failed to converge, increase the number of iterations.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "184 - GLM with avg smape 2.62: \n",
            "Model Number: 185 of 191 with model DatepartRegression for Validation 3\n",
            "185 - DatepartRegression with avg smape 3.81: \n",
            "Model Number: 186 of 191 with model GLM for Validation 3\n",
            "186 - GLM with avg smape 2.62: \n",
            "Model Number: 187 of 191 with model MultivariateMotif for Validation 3\n",
            "187 - MultivariateMotif with avg smape 8.93: \n",
            "Model Number: 188 of 191 with model GLM for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/genmod/families/family.py:1367: ValueWarning:\n",
            "\n",
            "Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "188 - GLM with avg smape 9.04: \n",
            "Model Number: 189 of 191 with model WindowRegression for Validation 3\n",
            "189 - WindowRegression with avg smape 3.88: \n",
            "Model Number: 190 of 191 with model Ensemble for Validation 3\n",
            "190 - Ensemble with avg smape 2.33: \n",
            "Model Number: 191 of 191 with model MultivariateMotif for Validation 3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/decomposition/_fastica.py:583: UserWarning:\n",
            "\n",
            "Ignoring n_components with whiten=False.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "191 - MultivariateMotif with avg smape 8.75: \n",
            "Model Number: 1843 with model Ensemble in generation 12 of Ensembles\n",
            "Model Number: 1844 with model Ensemble in generation 12 of Ensembles\n",
            "Model Number: 1845 with model Ensemble in generation 12 of Ensembles\n",
            "Model Number: 1846 with model Ensemble in generation 12 of Ensembles\n",
            "Model Number: 1847 with model Ensemble in generation 12 of Ensembles\n",
            "Model Number: 1848 with model Ensemble in generation 12 of Ensembles\n",
            "Model Number: 1849 with model Ensemble in generation 12 of Ensembles\n",
            "Model Number: 1850 with model Ensemble in generation 12 of Ensembles\n",
            "Validation Round: 1\n",
            "Model Number: 1 of 8 with model Ensemble for Validation 1\n",
            "📈 1 - Ensemble with avg smape 3.92: \n",
            "Model Number: 2 of 8 with model Ensemble for Validation 1\n",
            "2 - Ensemble with avg smape 5.0: \n",
            "Model Number: 3 of 8 with model Ensemble for Validation 1\n",
            "3 - Ensemble with avg smape 5.32: \n",
            "Model Number: 4 of 8 with model Ensemble for Validation 1\n",
            "4 - Ensemble with avg smape 6.58: \n",
            "Model Number: 5 of 8 with model Ensemble for Validation 1\n",
            "5 - Ensemble with avg smape 3.92: \n",
            "Model Number: 6 of 8 with model Ensemble for Validation 1\n",
            "6 - Ensemble with avg smape 4.94: \n",
            "Model Number: 7 of 8 with model Ensemble for Validation 1\n",
            "7 - Ensemble with avg smape 5.04: \n",
            "Model Number: 8 of 8 with model Ensemble for Validation 1\n",
            "8 - Ensemble with avg smape 5.08: \n",
            "Validation Round: 2\n",
            "Model Number: 1 of 8 with model Ensemble for Validation 2\n",
            "📈 1 - Ensemble with avg smape 13.96: \n",
            "Model Number: 2 of 8 with model Ensemble for Validation 2\n",
            "2 - Ensemble with avg smape 14.89: \n",
            "Model Number: 3 of 8 with model Ensemble for Validation 2\n",
            "📈 3 - Ensemble with avg smape 13.23: \n",
            "Model Number: 4 of 8 with model Ensemble for Validation 2\n",
            "📈 4 - Ensemble with avg smape 12.87: \n",
            "Model Number: 5 of 8 with model Ensemble for Validation 2\n",
            "5 - Ensemble with avg smape 13.96: \n",
            "Model Number: 6 of 8 with model Ensemble for Validation 2\n",
            "6 - Ensemble with avg smape 14.08: \n",
            "Model Number: 7 of 8 with model Ensemble for Validation 2\n",
            "7 - Ensemble with avg smape 13.12: \n",
            "Model Number: 8 of 8 with model Ensemble for Validation 2\n",
            "8 - Ensemble with avg smape 13.18: \n",
            "Validation Round: 3\n",
            "Model Number: 1 of 8 with model Ensemble for Validation 3\n",
            "📈 1 - Ensemble with avg smape 1.65: \n",
            "Model Number: 2 of 8 with model Ensemble for Validation 3\n",
            "2 - Ensemble with avg smape 1.69: \n",
            "Model Number: 3 of 8 with model Ensemble for Validation 3\n",
            "3 - Ensemble with avg smape 1.85: \n",
            "Model Number: 4 of 8 with model Ensemble for Validation 3\n",
            "4 - Ensemble with avg smape 1.86: \n",
            "Model Number: 5 of 8 with model Ensemble for Validation 3\n",
            "5 - Ensemble with avg smape 1.65: \n",
            "Model Number: 6 of 8 with model Ensemble for Validation 3\n",
            "6 - Ensemble with avg smape 1.77: \n",
            "Model Number: 7 of 8 with model Ensemble for Validation 3\n",
            "7 - Ensemble with avg smape 1.79: \n",
            "Model Number: 8 of 8 with model Ensemble for Validation 3\n",
            "8 - Ensemble with avg smape 1.8: \n",
            "                   Close\n",
            "2024-01-16  42503.669309\n",
            "2024-01-17  42568.092078\n",
            "2024-01-18  42632.312401\n",
            "2024-01-19  42696.758440\n",
            "2024-01-20  42761.287999\n",
            "2024-01-21  42826.103853\n",
            "2024-01-22  42891.194362\n",
            "2024-01-23  42955.980414\n",
            "2024-01-24  43020.369765\n",
            "2024-01-25  43084.615701\n",
            "2024-01-26  43149.069263\n",
            "2024-01-27  43213.852807\n",
            "2024-01-28  43279.060395\n",
            "2024-01-29  43344.772631\n",
            "2024-01-30  43411.078357\n",
            "2024-01-31  43478.047199\n",
            "2024-02-01  43545.772502\n",
            "2024-02-02  43614.342749\n",
            "2024-02-03  43683.968686\n",
            "2024-02-04  43754.778298\n",
            "2024-02-05  43826.810528\n",
            "2024-02-06  43899.960543\n",
            "2024-02-07  43973.915755\n",
            "2024-02-08  44048.985832\n",
            "2024-02-09  44125.221027\n",
            "2024-02-10  44202.976621\n",
            "2024-02-11  44282.124102\n",
            "2024-02-12  44362.680546\n",
            "2024-02-13  44444.278907\n",
            "2024-02-14  44526.685920\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "r0SndvtcEvMF"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}