machinehack-renew-power-hiring-hackathon-model.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## Introduction\n\n#### create a model to get an ideally functioning turbine’s expected rotor bearing temperature.","metadata":{}},{"cell_type":"code","source":"!pip install imbalanced-learn==0.7.0 -q\n!pip install --user pycaret[full] -q\n!pip install numba==0.53 -q","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:46:42.694626Z","iopub.execute_input":"2022-10-10T13:46:42.695622Z","iopub.status.idle":"2022-10-10T13:47:26.459580Z","shell.execute_reply.started":"2022-10-10T13:46:42.695586Z","shell.execute_reply":"2022-10-10T13:47:26.458408Z"},"trusted":true},"execution_count":4,"outputs":[{"name":"stdout","text":"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n\u001b[0m\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\nhypertools 0.8.0 requires scikit-learn>=0.24, but you have scikit-learn 0.23.2 which is incompatible.\u001b[0m\u001b[31m\n\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n\u001b[0m\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\nstumpy 1.11.1 requires numba>=0.54, but you have numba 0.53.0 which is incompatible.\nhypertools 0.8.0 requires scikit-learn>=0.24, but you have scikit-learn 0.23.2 which is incompatible.\ncudf 21.10.1 requires numba>=0.53.1, but you have numba 0.53.0 which is incompatible.\u001b[0m\u001b[31m\n\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n\u001b[0m","output_type":"stream"}]},{"cell_type":"code","source":"import pycaret\nfrom pycaret.regression import *","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:48:47.525877Z","iopub.execute_input":"2022-10-10T13:48:47.526243Z","iopub.status.idle":"2022-10-10T13:48:53.714405Z","shell.execute_reply.started":"2022-10-10T13:48:47.526207Z","shell.execute_reply":"2022-10-10T13:48:53.713307Z"},"trusted":true},"execution_count":5,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<style type='text/css'>\n.datatable table.frame { margin-bottom: 0; }\n.datatable table.frame thead { border-bottom: none; }\n.datatable table.frame tr.coltypes td {  color: #FFFFFF;  line-height: 6px;  padding: 0 0.5em;}\n.datatable .bool    { background: #DDDD99; }\n.datatable .object  { background: #565656; }\n.datatable .int     { background: #5D9E5D; }\n.datatable .float   { background: #4040CC; }\n.datatable .str     { background: #CC4040; }\n.datatable .time    { background: #40CC40; }\n.datatable .row_index {  background: var(--jp-border-color3);  border-right: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  font-size: 9px;}\n.datatable .frame tbody td { text-align: left; }\n.datatable .frame tr.coltypes .row_index {  background: var(--jp-border-color0);}\n.datatable th:nth-child(2) { padding-left: 12px; }\n.datatable .hellipsis {  color: var(--jp-cell-editor-border-color);}\n.datatable .vellipsis {  background: var(--jp-layout-color0);  color: var(--jp-cell-editor-border-color);}\n.datatable .na {  color: var(--jp-cell-editor-border-color);  font-size: 80%;}\n.datatable .sp {  opacity: 0.25;}\n.datatable .footer { font-size: 9px; }\n.datatable .frame_dimensions {  background: var(--jp-border-color3);  border-top: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  display: inline-block;  opacity: 0.6;  padding: 1px 10px 1px 5px;}\n</style>\n"},"metadata":{}}]},{"cell_type":"code","source":"!pip install metpy -q","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:48:55.547068Z","iopub.execute_input":"2022-10-10T13:48:55.547499Z","iopub.status.idle":"2022-10-10T13:49:09.096118Z","shell.execute_reply.started":"2022-10-10T13:48:55.547464Z","shell.execute_reply":"2022-10-10T13:49:09.094704Z"},"trusted":true},"execution_count":6,"outputs":[{"name":"stdout","text":"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n\u001b[0m","output_type":"stream"}]},{"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport seaborn as sns # visualization\nfrom matplotlib import pyplot as plt # visualization\n%matplotlib inline\nimport warnings\nwarnings.filterwarnings(\"ignore\")\nimport re\n#import klib\n\nfrom scipy.stats import skew, kurtosis\nfrom prettytable import PrettyTable\n#import umap\nimport math\nimport metpy.calc as mpcalc\nfrom sklearn.neighbors import KNeighborsRegressor","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-10-10T13:49:20.828466Z","iopub.execute_input":"2022-10-10T13:49:20.828815Z","iopub.status.idle":"2022-10-10T13:49:20.838072Z","shell.execute_reply.started":"2022-10-10T13:49:20.828784Z","shell.execute_reply":"2022-10-10T13:49:20.836973Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":"### Import train and test dataset","metadata":{}},{"cell_type":"code","source":"train=pd.read_csv(\"../input/renew-data-machinehack/train.csv\")\ntest=pd.read_csv(\"../input/renew-data-machinehack/test.csv\")","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:56:13.994340Z","iopub.execute_input":"2022-10-10T13:56:13.994705Z","iopub.status.idle":"2022-10-10T13:56:16.698382Z","shell.execute_reply.started":"2022-10-10T13:56:13.994676Z","shell.execute_reply":"2022-10-10T13:56:16.697340Z"},"trusted":true},"execution_count":20,"outputs":[]},{"cell_type":"markdown","source":"### Data pre-processing function","metadata":{}},{"cell_type":"code","source":"def pre_process(df):\n    \n    #change column names to lowercase\n    df=df.rename(columns={col:col.lower()   for col in df.columns.values})\n    \n    #calculate tip ratio\n    df['tip_ratio']=df['generator_speed']/df['wind_speed_raw']\n    \n    #convert angle to direction\n    df['cardinal_direction']=mpcalc.angle_to_direction(df['wind_direction_raw'], full=True)\n    \n    #check active power that is calculated by the converter is greater than raw active power\n    df['active-convert_pwr_grt_apwer']=(df['active_power_calculated_by_converter']>df['active_power_raw']).astype('int')\n    \n    #check reactive power that is calculated by the converter is greater than raw reactive power\n    df['reactive-convert_pwr_grt_reapwer']=(df['reactice_power_calculated_by_converter']>df['reactive_power']).astype('int')\n    \n    #check nacelle inside temperature greater than nacelle temperature\n    df['in_tmp_grt_out_tmp']=(df['nc1_inside_temp']>df['nacelle_temp']).astype('int')\n    \n    #calculate apparent power\n    df['apparent_power']=df.apply(lambda x: math.sqrt(x.active_power_raw**2+x.reactive_power**2), axis=1)\n    \n    \n    \n    \n    \"\"\"categorical columns list\"\"\"\n\n    grpcol=['turbine_id','cardinal_direction']\n\n    \"\"\"numerical columns list\"\"\"\n    numcols=['active_power_calculated_by_converter', 'active_power_raw',\n               'ambient_temperature', 'generator_speed', 'generator_winding_temp_max',\n               'grid_power10min_average', 'nc1_inside_temp', 'nacelle_temp',\n               'reactice_power_calculated_by_converter', 'reactive_power',\n               'wind_direction_raw', 'wind_speed_raw', 'wind_speed_turbulence',\n                 'tip_ratio','apparent_power'\n                   ]\n\n\n    \"\"\"group by numerical summary of each numerical column\"\"\"\n    def feature_eng(df):\n        for valcol in numcols:\n            df1=(df.groupby(grpcol)[valcol].agg({'min','median','mean','max'}).reset_index())\n            df1=(df1.rename(columns={c:valcol+'_'+c for c in df1.loc[:,df1.columns.str.\n                                                match(\"(min|median|mean|max)\")]}))\n            df=pd.merge(df,df1,on=grpcol,how='left')\n        return df  \n\n\n    df=feature_eng(df)\n    \n    \"\"\"\"\n    z-score outlier detection for numerical columns  \n    def outlier_z(df,x):\n        threshold = 3\n        out=[]\n        mean = np.mean(df[x])\n        std = np.std(df[x])\n        for i in df[x]:\n            if ((i-mean)/std) > threshold:\n                out.append(1)\n            else:\n                out.append(0)\n        return out\n    \n    for col in ['active_power_calculated_by_converter', 'active_power_raw',\n                   'ambient_temperature', 'generator_speed', 'generator_winding_temp_max',\n                   'grid_power10min_average', 'nc1_inside_temp', 'nacelle_temp',\n                   'reactice_power_calculated_by_converter', 'reactive_power',\n                   'wind_direction_raw', 'wind_speed_raw', 'wind_speed_turbulence',\n                           ]:\n        df[f\"{col}_outlier\"]= outlier_z(df,col)\n   \n    for col in ['active_power_calculated_by_converter', 'active_power_raw',\n                   'ambient_temperature', 'generator_speed', 'generator_winding_temp_max',\n                   'grid_power10min_average', 'nc1_inside_temp', 'nacelle_temp',\n                   'reactice_power_calculated_by_converter', 'reactive_power',\n                   'wind_direction_raw', 'wind_speed_raw', 'wind_speed_turbulence',\n                           ]:\n        df[f\"{col}_skewness\"]=df.groupby('turbine_id')[col].transform(pd.Series.skew)\n        df[f\"{col}_kurtosis\"]=df.groupby('turbine_id')[col].transform(pd.Series.kurt)\n        \n    \n    for col in ['active_power_calculated_by_converter', 'active_power_raw',\n                   'ambient_temperature', 'generator_speed', 'generator_winding_temp_max',\n                   'grid_power10min_average', 'nc1_inside_temp', 'nacelle_temp',\n                   'reactice_power_calculated_by_converter', 'reactive_power',\n                   'wind_direction_raw', 'wind_speed_raw', 'wind_speed_turbulence',\n                           ]:\n        df[f\"{col}_1_lag\"]=df[col].shift(1,fill_value=0)\n        \n    \"\"\"\n    \n    return df","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:56:16.700314Z","iopub.execute_input":"2022-10-10T13:56:16.700883Z","iopub.status.idle":"2022-10-10T13:56:16.714264Z","shell.execute_reply.started":"2022-10-10T13:56:16.700841Z","shell.execute_reply":"2022-10-10T13:56:16.713455Z"},"trusted":true},"execution_count":21,"outputs":[]},{"cell_type":"markdown","source":"### Apply pre-process steps to train function","metadata":{}},{"cell_type":"code","source":"train=pre_process(train)","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:56:21.204061Z","iopub.execute_input":"2022-10-10T13:56:21.204577Z","iopub.status.idle":"2022-10-10T13:56:51.198861Z","shell.execute_reply.started":"2022-10-10T13:56:21.204528Z","shell.execute_reply":"2022-10-10T13:56:51.197717Z"},"trusted":true},"execution_count":22,"outputs":[]},{"cell_type":"code","source":"for i,j in enumerate(train.columns.values):\n    print(f\"{i}_{j}\")  ","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:24:52.493653Z","iopub.execute_input":"2022-10-10T14:24:52.494048Z","iopub.status.idle":"2022-10-10T14:24:52.500836Z","shell.execute_reply.started":"2022-10-10T14:24:52.494016Z","shell.execute_reply":"2022-10-10T14:24:52.499696Z"},"trusted":true},"execution_count":37,"outputs":[{"name":"stdout","text":"0_timestamp\n1_active_power_calculated_by_converter\n2_active_power_raw\n3_ambient_temperature\n4_generator_speed\n5_generator_winding_temp_max\n6_grid_power10min_average\n7_nc1_inside_temp\n8_nacelle_temp\n9_reactice_power_calculated_by_converter\n10_reactive_power\n11_wind_direction_raw\n12_wind_speed_raw\n13_wind_speed_turbulence\n14_turbine_id\n15_target\n16_tip_ratio\n17_cardinal_direction\n18_active-convert_pwr_grt_apwer\n19_reactive-convert_pwr_grt_reapwer\n20_in_tmp_grt_out_tmp\n21_apparent_power\n22_active_power_calculated_by_converter_min\n23_active_power_calculated_by_converter_median\n24_active_power_calculated_by_converter_max\n25_active_power_calculated_by_converter_mean\n26_active_power_raw_min\n27_active_power_raw_median\n28_active_power_raw_max\n29_active_power_raw_mean\n30_ambient_temperature_min\n31_ambient_temperature_median\n32_ambient_temperature_max\n33_ambient_temperature_mean\n34_generator_speed_min\n35_generator_speed_median\n36_generator_speed_max\n37_generator_speed_mean\n38_generator_winding_temp_max_min\n39_generator_winding_temp_max_median\n40_generator_winding_temp_max_max\n41_generator_winding_temp_max_mean\n42_grid_power10min_average_min\n43_grid_power10min_average_median\n44_grid_power10min_average_max\n45_grid_power10min_average_mean\n46_nc1_inside_temp_min\n47_nc1_inside_temp_median\n48_nc1_inside_temp_max\n49_nc1_inside_temp_mean\n50_nacelle_temp_min\n51_nacelle_temp_median\n52_nacelle_temp_max\n53_nacelle_temp_mean\n54_reactice_power_calculated_by_converter_min\n55_reactice_power_calculated_by_converter_median\n56_reactice_power_calculated_by_converter_max\n57_reactice_power_calculated_by_converter_mean\n58_reactive_power_min\n59_reactive_power_median\n60_reactive_power_max\n61_reactive_power_mean\n62_wind_direction_raw_min\n63_wind_direction_raw_median\n64_wind_direction_raw_max\n65_wind_direction_raw_mean\n66_wind_speed_raw_min\n67_wind_speed_raw_median\n68_wind_speed_raw_max\n69_wind_speed_raw_mean\n70_wind_speed_turbulence_min\n71_wind_speed_turbulence_median\n72_wind_speed_turbulence_max\n73_wind_speed_turbulence_mean\n74_tip_ratio_min\n75_tip_ratio_median\n76_tip_ratio_max\n77_tip_ratio_mean\n78_apparent_power_min\n79_apparent_power_median\n80_apparent_power_max\n81_apparent_power_mean\n","output_type":"stream"}]},{"cell_type":"markdown","source":"### Split predictor and response variable","metadata":{}},{"cell_type":"code","source":"X=train.iloc[:,np.r_[1:15,16:82]]\ny=train['target']","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:57:27.924889Z","iopub.execute_input":"2022-10-10T13:57:27.925245Z","iopub.status.idle":"2022-10-10T13:57:29.270183Z","shell.execute_reply.started":"2022-10-10T13:57:27.925214Z","shell.execute_reply":"2022-10-10T13:57:29.269183Z"},"trusted":true},"execution_count":24,"outputs":[]},{"cell_type":"markdown","source":"### Creata a dataframe with selected variable","metadata":{}},{"cell_type":"code","source":"train1=pd.concat([X,y],axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:57:31.151015Z","iopub.execute_input":"2022-10-10T13:57:31.151409Z","iopub.status.idle":"2022-10-10T13:57:31.296122Z","shell.execute_reply.started":"2022-10-10T13:57:31.151374Z","shell.execute_reply":"2022-10-10T13:57:31.295168Z"},"trusted":true},"execution_count":25,"outputs":[]},{"cell_type":"markdown","source":"### Setup a pycaret model","metadata":{}},{"cell_type":"code","source":"reg_pycaret = setup(data = train1,\n                    data_split_shuffle=True,\n                    fold_strategy=\"kfold\",\n                    fold_shuffle=True,\n                    fold=5,\n                    target = 'target', session_id=112,\n                    use_gpu =True,\n                    silent=True\n                    ) \nset_config('seed', 123)","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:57:33.053329Z","iopub.execute_input":"2022-10-10T13:57:33.053689Z","iopub.status.idle":"2022-10-10T13:58:46.144552Z","shell.execute_reply.started":"2022-10-10T13:57:33.053658Z","shell.execute_reply":"2022-10-10T13:58:46.143582Z"},"trusted":true},"execution_count":26,"outputs":[{"output_type":"display_data","data":{"text/plain":"<pandas.io.formats.style.Styler at 0x7f9a5c99d250>","text/html":"<style type=\"text/css\">\n#T_ef2d4_row16_col1, #T_ef2d4_row42_col1 {\n  background-color: lightgreen;\n}\n</style>\n<table id=\"T_ef2d4_\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th class=\"col_heading level0 col0\" >Description</th>\n      <th class=\"col_heading level0 col1\" >Value</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_ef2d4_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_ef2d4_row0_col0\" class=\"data row0 col0\" >session_id</td>\n      <td id=\"T_ef2d4_row0_col1\" class=\"data row0 col1\" >112</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n      <td id=\"T_ef2d4_row1_col0\" class=\"data row1 col0\" >Target</td>\n      <td id=\"T_ef2d4_row1_col1\" class=\"data row1 col1\" >target</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n      <td id=\"T_ef2d4_row2_col0\" class=\"data row2 col0\" >Original Data</td>\n      <td id=\"T_ef2d4_row2_col1\" class=\"data row2 col1\" >(909604, 81)</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n      <td id=\"T_ef2d4_row3_col0\" class=\"data row3 col0\" >Missing Values</td>\n      <td id=\"T_ef2d4_row3_col1\" class=\"data row3 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n      <td id=\"T_ef2d4_row4_col0\" class=\"data row4 col0\" >Numeric Features</td>\n      <td id=\"T_ef2d4_row4_col1\" class=\"data row4 col1\" >75</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n      <td id=\"T_ef2d4_row5_col0\" class=\"data row5 col0\" >Categorical Features</td>\n      <td id=\"T_ef2d4_row5_col1\" class=\"data row5 col1\" >5</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n      <td id=\"T_ef2d4_row6_col0\" class=\"data row6 col0\" >Ordinal Features</td>\n      <td id=\"T_ef2d4_row6_col1\" class=\"data row6 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n      <td id=\"T_ef2d4_row7_col0\" class=\"data row7 col0\" >High Cardinality Features</td>\n      <td id=\"T_ef2d4_row7_col1\" class=\"data row7 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n      <td id=\"T_ef2d4_row8_col0\" class=\"data row8 col0\" >High Cardinality Method</td>\n      <td id=\"T_ef2d4_row8_col1\" class=\"data row8 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n      <td id=\"T_ef2d4_row9_col0\" class=\"data row9 col0\" >Transformed Train Set</td>\n      <td id=\"T_ef2d4_row9_col1\" class=\"data row9 col1\" >(636722, 101)</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n      <td id=\"T_ef2d4_row10_col0\" class=\"data row10 col0\" >Transformed Test Set</td>\n      <td id=\"T_ef2d4_row10_col1\" class=\"data row10 col1\" >(272882, 101)</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n      <td id=\"T_ef2d4_row11_col0\" class=\"data row11 col0\" >Shuffle Train-Test</td>\n      <td id=\"T_ef2d4_row11_col1\" class=\"data row11 col1\" >True</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n      <td id=\"T_ef2d4_row12_col0\" class=\"data row12 col0\" >Stratify Train-Test</td>\n      <td id=\"T_ef2d4_row12_col1\" class=\"data row12 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n      <td id=\"T_ef2d4_row13_col0\" class=\"data row13 col0\" >Fold Generator</td>\n      <td id=\"T_ef2d4_row13_col1\" class=\"data row13 col1\" >KFold</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n      <td id=\"T_ef2d4_row14_col0\" class=\"data row14 col0\" >Fold Number</td>\n      <td id=\"T_ef2d4_row14_col1\" class=\"data row14 col1\" >5</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n      <td id=\"T_ef2d4_row15_col0\" class=\"data row15 col0\" >CPU Jobs</td>\n      <td id=\"T_ef2d4_row15_col1\" class=\"data row15 col1\" >-1</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n      <td id=\"T_ef2d4_row16_col0\" class=\"data row16 col0\" >Use GPU</td>\n      <td id=\"T_ef2d4_row16_col1\" class=\"data row16 col1\" >True</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n      <td id=\"T_ef2d4_row17_col0\" class=\"data row17 col0\" >Log Experiment</td>\n      <td id=\"T_ef2d4_row17_col1\" class=\"data row17 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n      <td id=\"T_ef2d4_row18_col0\" class=\"data row18 col0\" >Experiment Name</td>\n      <td id=\"T_ef2d4_row18_col1\" class=\"data row18 col1\" >reg-default-name</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n      <td id=\"T_ef2d4_row19_col0\" class=\"data row19 col0\" >USI</td>\n      <td id=\"T_ef2d4_row19_col1\" class=\"data row19 col1\" >d48d</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n      <td id=\"T_ef2d4_row20_col0\" class=\"data row20 col0\" >Imputation Type</td>\n      <td id=\"T_ef2d4_row20_col1\" class=\"data row20 col1\" >simple</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n      <td id=\"T_ef2d4_row21_col0\" class=\"data row21 col0\" >Iterative Imputation Iteration</td>\n      <td id=\"T_ef2d4_row21_col1\" class=\"data row21 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n      <td id=\"T_ef2d4_row22_col0\" class=\"data row22 col0\" >Numeric Imputer</td>\n      <td id=\"T_ef2d4_row22_col1\" class=\"data row22 col1\" >mean</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n      <td id=\"T_ef2d4_row23_col0\" class=\"data row23 col0\" >Iterative Imputation Numeric Model</td>\n      <td id=\"T_ef2d4_row23_col1\" class=\"data row23 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n      <td id=\"T_ef2d4_row24_col0\" class=\"data row24 col0\" >Categorical Imputer</td>\n      <td id=\"T_ef2d4_row24_col1\" class=\"data row24 col1\" >constant</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n      <td id=\"T_ef2d4_row25_col0\" class=\"data row25 col0\" >Iterative Imputation Categorical Model</td>\n      <td id=\"T_ef2d4_row25_col1\" class=\"data row25 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n      <td id=\"T_ef2d4_row26_col0\" class=\"data row26 col0\" >Unknown Categoricals Handling</td>\n      <td id=\"T_ef2d4_row26_col1\" class=\"data row26 col1\" >least_frequent</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n      <td id=\"T_ef2d4_row27_col0\" class=\"data row27 col0\" >Normalize</td>\n      <td id=\"T_ef2d4_row27_col1\" class=\"data row27 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n      <td id=\"T_ef2d4_row28_col0\" class=\"data row28 col0\" >Normalize Method</td>\n      <td id=\"T_ef2d4_row28_col1\" class=\"data row28 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n      <td id=\"T_ef2d4_row29_col0\" class=\"data row29 col0\" >Transformation</td>\n      <td id=\"T_ef2d4_row29_col1\" class=\"data row29 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n      <td id=\"T_ef2d4_row30_col0\" class=\"data row30 col0\" >Transformation Method</td>\n      <td id=\"T_ef2d4_row30_col1\" class=\"data row30 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n      <td id=\"T_ef2d4_row31_col0\" class=\"data row31 col0\" >PCA</td>\n      <td id=\"T_ef2d4_row31_col1\" class=\"data row31 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n      <td id=\"T_ef2d4_row32_col0\" class=\"data row32 col0\" >PCA Method</td>\n      <td id=\"T_ef2d4_row32_col1\" class=\"data row32 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n      <td id=\"T_ef2d4_row33_col0\" class=\"data row33 col0\" >PCA Components</td>\n      <td id=\"T_ef2d4_row33_col1\" class=\"data row33 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n      <td id=\"T_ef2d4_row34_col0\" class=\"data row34 col0\" >Ignore Low Variance</td>\n      <td id=\"T_ef2d4_row34_col1\" class=\"data row34 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n      <td id=\"T_ef2d4_row35_col0\" class=\"data row35 col0\" >Combine Rare Levels</td>\n      <td id=\"T_ef2d4_row35_col1\" class=\"data row35 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n      <td id=\"T_ef2d4_row36_col0\" class=\"data row36 col0\" >Rare Level Threshold</td>\n      <td id=\"T_ef2d4_row36_col1\" class=\"data row36 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n      <td id=\"T_ef2d4_row37_col0\" class=\"data row37 col0\" >Numeric Binning</td>\n      <td id=\"T_ef2d4_row37_col1\" class=\"data row37 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n      <td id=\"T_ef2d4_row38_col0\" class=\"data row38 col0\" >Remove Outliers</td>\n      <td id=\"T_ef2d4_row38_col1\" class=\"data row38 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n      <td id=\"T_ef2d4_row39_col0\" class=\"data row39 col0\" >Outliers Threshold</td>\n      <td id=\"T_ef2d4_row39_col1\" class=\"data row39 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n      <td id=\"T_ef2d4_row40_col0\" class=\"data row40 col0\" >Remove Multicollinearity</td>\n      <td id=\"T_ef2d4_row40_col1\" class=\"data row40 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n      <td id=\"T_ef2d4_row41_col0\" class=\"data row41 col0\" >Multicollinearity Threshold</td>\n      <td id=\"T_ef2d4_row41_col1\" class=\"data row41 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n      <td id=\"T_ef2d4_row42_col0\" class=\"data row42 col0\" >Remove Perfect Collinearity</td>\n      <td id=\"T_ef2d4_row42_col1\" class=\"data row42 col1\" >True</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n      <td id=\"T_ef2d4_row43_col0\" class=\"data row43 col0\" >Clustering</td>\n      <td id=\"T_ef2d4_row43_col1\" class=\"data row43 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n      <td id=\"T_ef2d4_row44_col0\" class=\"data row44 col0\" >Clustering Iteration</td>\n      <td id=\"T_ef2d4_row44_col1\" class=\"data row44 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n      <td id=\"T_ef2d4_row45_col0\" class=\"data row45 col0\" >Polynomial Features</td>\n      <td id=\"T_ef2d4_row45_col1\" class=\"data row45 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n      <td id=\"T_ef2d4_row46_col0\" class=\"data row46 col0\" >Polynomial Degree</td>\n      <td id=\"T_ef2d4_row46_col1\" class=\"data row46 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n      <td id=\"T_ef2d4_row47_col0\" class=\"data row47 col0\" >Trignometry Features</td>\n      <td id=\"T_ef2d4_row47_col1\" class=\"data row47 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row48\" class=\"row_heading level0 row48\" >48</th>\n      <td id=\"T_ef2d4_row48_col0\" class=\"data row48 col0\" >Polynomial Threshold</td>\n      <td id=\"T_ef2d4_row48_col1\" class=\"data row48 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row49\" class=\"row_heading level0 row49\" >49</th>\n      <td id=\"T_ef2d4_row49_col0\" class=\"data row49 col0\" >Group Features</td>\n      <td id=\"T_ef2d4_row49_col1\" class=\"data row49 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row50\" class=\"row_heading level0 row50\" >50</th>\n      <td id=\"T_ef2d4_row50_col0\" class=\"data row50 col0\" >Feature Selection</td>\n      <td id=\"T_ef2d4_row50_col1\" class=\"data row50 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row51\" class=\"row_heading level0 row51\" >51</th>\n      <td id=\"T_ef2d4_row51_col0\" class=\"data row51 col0\" >Feature Selection Method</td>\n      <td id=\"T_ef2d4_row51_col1\" class=\"data row51 col1\" >classic</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row52\" class=\"row_heading level0 row52\" >52</th>\n      <td id=\"T_ef2d4_row52_col0\" class=\"data row52 col0\" >Features Selection Threshold</td>\n      <td id=\"T_ef2d4_row52_col1\" class=\"data row52 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row53\" class=\"row_heading level0 row53\" >53</th>\n      <td id=\"T_ef2d4_row53_col0\" class=\"data row53 col0\" >Feature Interaction</td>\n      <td id=\"T_ef2d4_row53_col1\" class=\"data row53 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row54\" class=\"row_heading level0 row54\" >54</th>\n      <td id=\"T_ef2d4_row54_col0\" class=\"data row54 col0\" >Feature Ratio</td>\n      <td id=\"T_ef2d4_row54_col1\" class=\"data row54 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row55\" class=\"row_heading level0 row55\" >55</th>\n      <td id=\"T_ef2d4_row55_col0\" class=\"data row55 col0\" >Interaction Threshold</td>\n      <td id=\"T_ef2d4_row55_col1\" class=\"data row55 col1\" >None</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row56\" class=\"row_heading level0 row56\" >56</th>\n      <td id=\"T_ef2d4_row56_col0\" class=\"data row56 col0\" >Transform Target</td>\n      <td id=\"T_ef2d4_row56_col1\" class=\"data row56 col1\" >False</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef2d4_level0_row57\" class=\"row_heading level0 row57\" >57</th>\n      <td id=\"T_ef2d4_row57_col0\" class=\"data row57 col0\" >Transform Target Method</td>\n      <td id=\"T_ef2d4_row57_col1\" class=\"data row57 col1\" >box-cox</td>\n    </tr>\n  </tbody>\n</table>\n"},"metadata":{}}]},{"cell_type":"markdown","source":"### Compare multiple regression models and select the top 3 models based on the evaluation metric MAPE.","metadata":{}},{"cell_type":"code","source":"top3 = compare_models(sort = 'MAPE',n_select=3,exclude=['rf','dt','ada','et','huber','gbr','par'])","metadata":{"execution":{"iopub.status.busy":"2022-10-10T13:59:15.508495Z","iopub.execute_input":"2022-10-10T13:59:15.508850Z","iopub.status.idle":"2022-10-10T14:04:37.217998Z","shell.execute_reply.started":"2022-10-10T13:59:15.508820Z","shell.execute_reply":"2022-10-10T14:04:37.217050Z"},"trusted":true},"execution_count":27,"outputs":[{"output_type":"display_data","data":{"text/plain":"<pandas.io.formats.style.Styler at 0x7f9bd37d1390>","text/html":"<style type=\"text/css\">\n#T_88665_ th {\n  text-align: left;\n}\n#T_88665_row0_col0, #T_88665_row0_col2, #T_88665_row0_col3, #T_88665_row0_col4, #T_88665_row0_col5, #T_88665_row1_col0, #T_88665_row1_col1, #T_88665_row1_col6, #T_88665_row2_col0, #T_88665_row2_col1, #T_88665_row2_col2, #T_88665_row2_col3, #T_88665_row2_col4, #T_88665_row2_col5, #T_88665_row2_col6, #T_88665_row3_col0, #T_88665_row3_col1, #T_88665_row3_col2, #T_88665_row3_col3, #T_88665_row3_col4, 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<tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th class=\"col_heading level0 col0\" >Model</th>\n      <th class=\"col_heading level0 col1\" >MAE</th>\n      <th class=\"col_heading level0 col2\" >MSE</th>\n      <th class=\"col_heading level0 col3\" >RMSE</th>\n      <th class=\"col_heading level0 col4\" >R2</th>\n      <th class=\"col_heading level0 col5\" >RMSLE</th>\n      <th class=\"col_heading level0 col6\" >MAPE</th>\n      <th class=\"col_heading level0 col7\" >TT (Sec)</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_88665_level0_row0\" class=\"row_heading level0 row0\" >xgboost</th>\n      <td id=\"T_88665_row0_col0\" class=\"data row0 col0\" >Extreme Gradient Boosting</td>\n      <td id=\"T_88665_row0_col1\" class=\"data row0 col1\" >0.8855</td>\n      <td id=\"T_88665_row0_col2\" class=\"data row0 col2\" >1.7207</td>\n      <td id=\"T_88665_row0_col3\" class=\"data row0 col3\" >1.3117</td>\n      <td id=\"T_88665_row0_col4\" class=\"data row0 col4\" >0.7486</td>\n      <td id=\"T_88665_row0_col5\" class=\"data row0 col5\" >0.0273</td>\n      <td id=\"T_88665_row0_col6\" class=\"data row0 col6\" >0.0190</td>\n      <td id=\"T_88665_row0_col7\" class=\"data row0 col7\" >3.8520</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row1\" class=\"row_heading level0 row1\" >catboost</th>\n      <td id=\"T_88665_row1_col0\" class=\"data row1 col0\" >CatBoost Regressor</td>\n      <td id=\"T_88665_row1_col1\" class=\"data row1 col1\" >0.8869</td>\n      <td id=\"T_88665_row1_col2\" class=\"data row1 col2\" >1.7129</td>\n      <td id=\"T_88665_row1_col3\" class=\"data row1 col3\" >1.3088</td>\n      <td id=\"T_88665_row1_col4\" class=\"data row1 col4\" >0.7498</td>\n      <td id=\"T_88665_row1_col5\" class=\"data row1 col5\" >0.0272</td>\n      <td id=\"T_88665_row1_col6\" class=\"data row1 col6\" >0.0191</td>\n      <td id=\"T_88665_row1_col7\" class=\"data row1 col7\" >26.2020</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row2\" class=\"row_heading level0 row2\" >lightgbm</th>\n      <td id=\"T_88665_row2_col0\" class=\"data row2 col0\" >Light Gradient Boosting Machine</td>\n      <td id=\"T_88665_row2_col1\" class=\"data row2 col1\" >0.9480</td>\n      <td id=\"T_88665_row2_col2\" class=\"data row2 col2\" >1.9353</td>\n      <td id=\"T_88665_row2_col3\" class=\"data row2 col3\" >1.3911</td>\n      <td id=\"T_88665_row2_col4\" class=\"data row2 col4\" >0.7173</td>\n      <td id=\"T_88665_row2_col5\" class=\"data row2 col5\" >0.0289</td>\n      <td id=\"T_88665_row2_col6\" class=\"data row2 col6\" >0.0204</td>\n      <td id=\"T_88665_row2_col7\" class=\"data row2 col7\" >9.0580</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row3\" class=\"row_heading level0 row3\" >br</th>\n      <td id=\"T_88665_row3_col0\" class=\"data row3 col0\" >Bayesian Ridge</td>\n      <td id=\"T_88665_row3_col1\" class=\"data row3 col1\" >1.1740</td>\n      <td id=\"T_88665_row3_col2\" class=\"data row3 col2\" >2.8389</td>\n      <td id=\"T_88665_row3_col3\" class=\"data row3 col3\" >1.6849</td>\n      <td id=\"T_88665_row3_col4\" class=\"data row3 col4\" >0.5853</td>\n      <td id=\"T_88665_row3_col5\" class=\"data row3 col5\" >0.0347</td>\n      <td id=\"T_88665_row3_col6\" class=\"data row3 col6\" >0.0251</td>\n      <td id=\"T_88665_row3_col7\" class=\"data row3 col7\" >9.8880</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row4\" class=\"row_heading level0 row4\" >omp</th>\n      <td id=\"T_88665_row4_col0\" class=\"data row4 col0\" >Orthogonal Matching Pursuit</td>\n      <td id=\"T_88665_row4_col1\" class=\"data row4 col1\" >1.2666</td>\n      <td id=\"T_88665_row4_col2\" class=\"data row4 col2\" >3.1716</td>\n      <td id=\"T_88665_row4_col3\" class=\"data row4 col3\" >1.7809</td>\n      <td id=\"T_88665_row4_col4\" class=\"data row4 col4\" >0.5367</td>\n      <td id=\"T_88665_row4_col5\" class=\"data row4 col5\" >0.0368</td>\n      <td id=\"T_88665_row4_col6\" class=\"data row4 col6\" >0.0271</td>\n      <td id=\"T_88665_row4_col7\" class=\"data row4 col7\" >0.8300</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row5\" class=\"row_heading level0 row5\" >en</th>\n      <td id=\"T_88665_row5_col0\" class=\"data row5 col0\" >Elastic Net</td>\n      <td id=\"T_88665_row5_col1\" class=\"data row5 col1\" >1.3312</td>\n      <td id=\"T_88665_row5_col2\" class=\"data row5 col2\" >3.6257</td>\n      <td id=\"T_88665_row5_col3\" class=\"data row5 col3\" >1.9041</td>\n      <td id=\"T_88665_row5_col4\" class=\"data row5 col4\" >0.4703</td>\n      <td id=\"T_88665_row5_col5\" class=\"data row5 col5\" >0.0393</td>\n      <td id=\"T_88665_row5_col6\" class=\"data row5 col6\" >0.0285</td>\n      <td id=\"T_88665_row5_col7\" class=\"data row5 col7\" >0.6480</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row6\" class=\"row_heading level0 row6\" >lasso</th>\n      <td id=\"T_88665_row6_col0\" class=\"data row6 col0\" >Lasso Regression</td>\n      <td id=\"T_88665_row6_col1\" class=\"data row6 col1\" >1.3675</td>\n      <td id=\"T_88665_row6_col2\" class=\"data row6 col2\" >3.8313</td>\n      <td id=\"T_88665_row6_col3\" class=\"data row6 col3\" >1.9574</td>\n      <td id=\"T_88665_row6_col4\" class=\"data row6 col4\" >0.4403</td>\n      <td id=\"T_88665_row6_col5\" class=\"data row6 col5\" >0.0404</td>\n      <td id=\"T_88665_row6_col6\" class=\"data row6 col6\" >0.0293</td>\n      <td id=\"T_88665_row6_col7\" class=\"data row6 col7\" >0.6000</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row7\" class=\"row_heading level0 row7\" >knn</th>\n      <td id=\"T_88665_row7_col0\" class=\"data row7 col0\" >K Neighbors Regressor</td>\n      <td id=\"T_88665_row7_col1\" class=\"data row7 col1\" >1.3952</td>\n      <td id=\"T_88665_row7_col2\" class=\"data row7 col2\" >3.7906</td>\n      <td id=\"T_88665_row7_col3\" class=\"data row7 col3\" >1.9469</td>\n      <td id=\"T_88665_row7_col4\" class=\"data row7 col4\" >0.4463</td>\n      <td id=\"T_88665_row7_col5\" class=\"data row7 col5\" >0.0407</td>\n      <td id=\"T_88665_row7_col6\" class=\"data row7 col6\" >0.0301</td>\n      <td id=\"T_88665_row7_col7\" class=\"data row7 col7\" >3.3800</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row8\" class=\"row_heading level0 row8\" >ridge</th>\n      <td id=\"T_88665_row8_col0\" class=\"data row8 col0\" >Ridge Regression</td>\n      <td id=\"T_88665_row8_col1\" class=\"data row8 col1\" >1.5145</td>\n      <td id=\"T_88665_row8_col2\" class=\"data row8 col2\" >4.1408</td>\n      <td id=\"T_88665_row8_col3\" class=\"data row8 col3\" >2.0324</td>\n      <td id=\"T_88665_row8_col4\" class=\"data row8 col4\" >0.3949</td>\n      <td id=\"T_88665_row8_col5\" class=\"data row8 col5\" >0.0423</td>\n      <td id=\"T_88665_row8_col6\" class=\"data row8 col6\" >0.0325</td>\n      <td id=\"T_88665_row8_col7\" class=\"data row8 col7\" >0.4040</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row9\" class=\"row_heading level0 row9\" >lr</th>\n      <td id=\"T_88665_row9_col0\" class=\"data row9 col0\" >Linear Regression</td>\n      <td id=\"T_88665_row9_col1\" class=\"data row9 col1\" >1.5544</td>\n      <td id=\"T_88665_row9_col2\" class=\"data row9 col2\" >4.4717</td>\n      <td id=\"T_88665_row9_col3\" class=\"data row9 col3\" >2.0838</td>\n      <td id=\"T_88665_row9_col4\" class=\"data row9 col4\" >0.3470</td>\n      <td id=\"T_88665_row9_col5\" class=\"data row9 col5\" >0.0434</td>\n      <td id=\"T_88665_row9_col6\" class=\"data row9 col6\" >0.0334</td>\n      <td id=\"T_88665_row9_col7\" class=\"data row9 col7\" >1.0160</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row10\" class=\"row_heading level0 row10\" >llar</th>\n      <td id=\"T_88665_row10_col0\" class=\"data row10 col0\" >Lasso Least Angle Regression</td>\n      <td id=\"T_88665_row10_col1\" class=\"data row10 col1\" >1.9015</td>\n      <td id=\"T_88665_row10_col2\" class=\"data row10 col2\" >6.8458</td>\n      <td id=\"T_88665_row10_col3\" class=\"data row10 col3\" >2.6164</td>\n      <td id=\"T_88665_row10_col4\" class=\"data row10 col4\" >-0.0000</td>\n      <td id=\"T_88665_row10_col5\" class=\"data row10 col5\" >0.0547</td>\n      <td id=\"T_88665_row10_col6\" class=\"data row10 col6\" >0.0411</td>\n      <td id=\"T_88665_row10_col7\" class=\"data row10 col7\" >0.8840</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row11\" class=\"row_heading level0 row11\" >dummy</th>\n      <td id=\"T_88665_row11_col0\" class=\"data row11 col0\" >Dummy Regressor</td>\n      <td id=\"T_88665_row11_col1\" class=\"data row11 col1\" >1.9015</td>\n      <td id=\"T_88665_row11_col2\" class=\"data row11 col2\" >6.8458</td>\n      <td id=\"T_88665_row11_col3\" class=\"data row11 col3\" >2.6164</td>\n      <td id=\"T_88665_row11_col4\" class=\"data row11 col4\" >-0.0000</td>\n      <td id=\"T_88665_row11_col5\" class=\"data row11 col5\" >0.0547</td>\n      <td id=\"T_88665_row11_col6\" class=\"data row11 col6\" >0.0411</td>\n      <td id=\"T_88665_row11_col7\" class=\"data row11 col7\" >0.2740</td>\n    </tr>\n    <tr>\n      <th id=\"T_88665_level0_row12\" class=\"row_heading level0 row12\" >lar</th>\n      <td id=\"T_88665_row12_col0\" class=\"data row12 col0\" >Least Angle Regression</td>\n      <td id=\"T_88665_row12_col1\" class=\"data row12 col1\" >1365623040.8293</td>\n      <td id=\"T_88665_row12_col2\" class=\"data row12 col2\" >45754312498994880512.0000</td>\n      <td id=\"T_88665_row12_col3\" class=\"data row12 col3\" >3029105862.1161</td>\n      <td id=\"T_88665_row12_col4\" class=\"data row12 col4\" >-6666998181120346112.0000</td>\n      <td id=\"T_88665_row12_col5\" class=\"data row12 col5\" >9.6135</td>\n      <td id=\"T_88665_row12_col6\" class=\"data row12 col6\" >29809131.3006</td>\n      <td id=\"T_88665_row12_col7\" class=\"data row12 col7\" >0.8780</td>\n    </tr>\n  </tbody>\n</table>\n"},"metadata":{}}]},{"cell_type":"markdown","source":"### Blend the top 3 models.","metadata":{}},{"cell_type":"code","source":"blender = blend_models(top3)","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:04:43.025136Z","iopub.execute_input":"2022-10-10T14:04:43.025830Z","iopub.status.idle":"2022-10-10T14:06:53.760870Z","shell.execute_reply.started":"2022-10-10T14:04:43.025793Z","shell.execute_reply":"2022-10-10T14:06:53.759925Z"},"trusted":true},"execution_count":28,"outputs":[{"output_type":"display_data","data":{"text/plain":"<pandas.io.formats.style.Styler at 0x7f9ac7f49ad0>","text/html":"<style type=\"text/css\">\n#T_ef45c_row5_col0, #T_ef45c_row5_col1, #T_ef45c_row5_col2, #T_ef45c_row5_col3, #T_ef45c_row5_col4, #T_ef45c_row5_col5 {\n  background: yellow;\n}\n</style>\n<table id=\"T_ef45c_\">\n  <thead>\n    <tr>\n      <th class=\"blank level0\" >&nbsp;</th>\n      <th class=\"col_heading level0 col0\" >MAE</th>\n      <th class=\"col_heading level0 col1\" >MSE</th>\n      <th class=\"col_heading level0 col2\" >RMSE</th>\n      <th class=\"col_heading level0 col3\" >R2</th>\n      <th class=\"col_heading level0 col4\" >RMSLE</th>\n      <th class=\"col_heading level0 col5\" >MAPE</th>\n    </tr>\n    <tr>\n      <th class=\"index_name level0\" >Fold</th>\n      <th class=\"blank col0\" >&nbsp;</th>\n      <th class=\"blank col1\" >&nbsp;</th>\n      <th class=\"blank col2\" >&nbsp;</th>\n      <th class=\"blank col3\" >&nbsp;</th>\n      <th class=\"blank col4\" >&nbsp;</th>\n      <th class=\"blank col5\" >&nbsp;</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_ef45c_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n      <td id=\"T_ef45c_row0_col0\" class=\"data row0 col0\" >0.8891</td>\n      <td id=\"T_ef45c_row0_col1\" class=\"data row0 col1\" >1.7142</td>\n      <td id=\"T_ef45c_row0_col2\" class=\"data row0 col2\" >1.3093</td>\n      <td id=\"T_ef45c_row0_col3\" class=\"data row0 col3\" >0.7482</td>\n      <td id=\"T_ef45c_row0_col4\" class=\"data row0 col4\" >0.0272</td>\n      <td id=\"T_ef45c_row0_col5\" class=\"data row0 col5\" >0.0191</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef45c_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n      <td id=\"T_ef45c_row1_col0\" class=\"data row1 col0\" >0.8901</td>\n      <td id=\"T_ef45c_row1_col1\" class=\"data row1 col1\" >1.7258</td>\n      <td id=\"T_ef45c_row1_col2\" class=\"data row1 col2\" >1.3137</td>\n      <td id=\"T_ef45c_row1_col3\" class=\"data row1 col3\" >0.7478</td>\n      <td id=\"T_ef45c_row1_col4\" class=\"data row1 col4\" >0.0274</td>\n      <td id=\"T_ef45c_row1_col5\" class=\"data row1 col5\" >0.0191</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef45c_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n      <td id=\"T_ef45c_row2_col0\" class=\"data row2 col0\" >0.8913</td>\n      <td id=\"T_ef45c_row2_col1\" class=\"data row2 col1\" >1.7385</td>\n      <td id=\"T_ef45c_row2_col2\" class=\"data row2 col2\" >1.3185</td>\n      <td id=\"T_ef45c_row2_col3\" class=\"data row2 col3\" >0.7440</td>\n      <td id=\"T_ef45c_row2_col4\" class=\"data row2 col4\" >0.0275</td>\n      <td id=\"T_ef45c_row2_col5\" class=\"data row2 col5\" >0.0192</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef45c_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n      <td id=\"T_ef45c_row3_col0\" class=\"data row3 col0\" >0.8884</td>\n      <td id=\"T_ef45c_row3_col1\" class=\"data row3 col1\" >1.7293</td>\n      <td id=\"T_ef45c_row3_col2\" class=\"data row3 col2\" >1.3150</td>\n      <td id=\"T_ef45c_row3_col3\" class=\"data row3 col3\" >0.7480</td>\n      <td id=\"T_ef45c_row3_col4\" class=\"data row3 col4\" >0.0273</td>\n      <td id=\"T_ef45c_row3_col5\" class=\"data row3 col5\" >0.0191</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef45c_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n      <td id=\"T_ef45c_row4_col0\" class=\"data row4 col0\" >0.8964</td>\n      <td id=\"T_ef45c_row4_col1\" class=\"data row4 col1\" >1.7481</td>\n      <td id=\"T_ef45c_row4_col2\" class=\"data row4 col2\" >1.3222</td>\n      <td id=\"T_ef45c_row4_col3\" class=\"data row4 col3\" >0.7476</td>\n      <td id=\"T_ef45c_row4_col4\" class=\"data row4 col4\" >0.0275</td>\n      <td id=\"T_ef45c_row4_col5\" class=\"data row4 col5\" >0.0192</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef45c_level0_row5\" class=\"row_heading level0 row5\" >Mean</th>\n      <td id=\"T_ef45c_row5_col0\" class=\"data row5 col0\" >0.8910</td>\n      <td id=\"T_ef45c_row5_col1\" class=\"data row5 col1\" >1.7312</td>\n      <td id=\"T_ef45c_row5_col2\" class=\"data row5 col2\" >1.3157</td>\n      <td id=\"T_ef45c_row5_col3\" class=\"data row5 col3\" >0.7471</td>\n      <td id=\"T_ef45c_row5_col4\" class=\"data row5 col4\" >0.0274</td>\n      <td id=\"T_ef45c_row5_col5\" class=\"data row5 col5\" >0.0191</td>\n    </tr>\n    <tr>\n      <th id=\"T_ef45c_level0_row6\" class=\"row_heading level0 row6\" >Std</th>\n      <td id=\"T_ef45c_row6_col0\" class=\"data row6 col0\" >0.0029</td>\n      <td id=\"T_ef45c_row6_col1\" class=\"data row6 col1\" >0.0115</td>\n      <td id=\"T_ef45c_row6_col2\" class=\"data row6 col2\" >0.0044</td>\n      <td id=\"T_ef45c_row6_col3\" class=\"data row6 col3\" >0.0016</td>\n      <td id=\"T_ef45c_row6_col4\" class=\"data row6 col4\" >0.0001</td>\n      <td id=\"T_ef45c_row6_col5\" class=\"data row6 col5\" >0.0001</td>\n    </tr>\n  </tbody>\n</table>\n"},"metadata":{}}]},{"cell_type":"markdown","source":"### Finalize the model","metadata":{}},{"cell_type":"code","source":"final = finalize_model(blender)","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:07:05.664391Z","iopub.execute_input":"2022-10-10T14:07:05.665081Z","iopub.status.idle":"2022-10-10T14:09:46.282057Z","shell.execute_reply.started":"2022-10-10T14:07:05.665047Z","shell.execute_reply":"2022-10-10T14:09:46.281074Z"},"trusted":true},"execution_count":29,"outputs":[]},{"cell_type":"code","source":"from sklearn import set_config\nset_config(display=\"diagram\")","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:09:56.195674Z","iopub.execute_input":"2022-10-10T14:09:56.196040Z","iopub.status.idle":"2022-10-10T14:09:56.200758Z","shell.execute_reply.started":"2022-10-10T14:09:56.196011Z","shell.execute_reply":"2022-10-10T14:09:56.199629Z"},"trusted":true},"execution_count":30,"outputs":[]},{"cell_type":"code","source":"final","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:09:57.712363Z","iopub.execute_input":"2022-10-10T14:09:57.712729Z","iopub.status.idle":"2022-10-10T14:09:57.734609Z","shell.execute_reply.started":"2022-10-10T14:09:57.712698Z","shell.execute_reply":"2022-10-10T14:09:57.733425Z"},"trusted":true},"execution_count":31,"outputs":[{"execution_count":31,"output_type":"execute_result","data":{"text/plain":"VotingRegressor(estimators=[('xgboost',\n                             XGBRegressor(base_score=0.5, booster='gbtree',\n                                          callbacks=None, colsample_bylevel=1,\n                                          colsample_bynode=1,\n                                          colsample_bytree=1,\n                                          early_stopping_rounds=None,\n                                          enable_categorical=False,\n                                          eval_metric=None, gamma=0, gpu_id=0,\n                                          grow_policy='depthwise',\n                                          importance_type=None,\n                                          interaction_constraints='',\n                                          learning_rate=0.300000012,\n                                          max_bin=2...\n                                           colsample_bytree=1.0, device='gpu',\n                                           importance_type='split',\n                                           learning_rate=0.1, max_depth=-1,\n                                           min_child_samples=20,\n                                           min_child_weight=0.001,\n                                           min_split_gain=0.0, n_estimators=100,\n                                           n_jobs=-1, num_leaves=31,\n                                           objective=None, random_state=112,\n                                           reg_alpha=0.0, reg_lambda=0.0,\n                                           silent='warn', subsample=1.0,\n                                           subsample_for_bin=200000,\n                                           subsample_freq=0))],\n                n_jobs=1, verbose=False, weights=None)","text/html":"<style>div.sk-top-container {color: black;background-color: white;}div.sk-toggleable {background-color: white;}label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.2em 0.3em;box-sizing: border-box;text-align: center;}div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}div.sk-estimator {font-family: monospace;background-color: #f0f8ff;margin: 0.25em 0.25em;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;}div.sk-estimator:hover {background-color: #d4ebff;}div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;}div.sk-item {z-index: 1;}div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}div.sk-parallel-item:only-child::after {width: 0;}div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0.2em;box-sizing: border-box;padding-bottom: 0.1em;background-color: white;position: relative;}div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}div.sk-label-container {position: relative;z-index: 2;text-align: center;}div.sk-container {display: inline-block;position: relative;}</style><div class=\"sk-top-container\"><div class=\"sk-container\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"de6c995a-a138-4e50-9b6c-9334ed32ae0c\" type=\"checkbox\" ><label class=\"sk-toggleable__label\" for=\"de6c995a-a138-4e50-9b6c-9334ed32ae0c\">VotingRegressor</label><div class=\"sk-toggleable__content\"><pre>VotingRegressor(estimators=[('xgboost',\n                             XGBRegressor(base_score=0.5, booster='gbtree',\n                                          callbacks=None, colsample_bylevel=1,\n                                          colsample_bynode=1,\n                                          colsample_bytree=1,\n                                          early_stopping_rounds=None,\n                                          enable_categorical=False,\n                                          eval_metric=None, gamma=0, gpu_id=0,\n                                          grow_policy='depthwise',\n                                          importance_type=None,\n                                          interaction_constraints='',\n                                          learning_rate=0.300000012,\n                                          max_bin=2...\n                                           colsample_bytree=1.0, device='gpu',\n                                           importance_type='split',\n                                           learning_rate=0.1, max_depth=-1,\n                                           min_child_samples=20,\n                                           min_child_weight=0.001,\n                                           min_split_gain=0.0, n_estimators=100,\n                                           n_jobs=-1, num_leaves=31,\n                                           objective=None, random_state=112,\n                                           reg_alpha=0.0, reg_lambda=0.0,\n                                           silent='warn', subsample=1.0,\n                                           subsample_for_bin=200000,\n                                           subsample_freq=0))],\n                n_jobs=1, verbose=False, weights=None)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>xgboost</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"0c66610e-1642-4fa9-a683-20b6742ea3fb\" type=\"checkbox\" ><label class=\"sk-toggleable__label\" for=\"0c66610e-1642-4fa9-a683-20b6742ea3fb\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=0.5, booster='gbtree', callbacks=None,\n             colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n             early_stopping_rounds=None, enable_categorical=False,\n             eval_metric=None, gamma=0, gpu_id=0, grow_policy='depthwise',\n             importance_type=None, interaction_constraints='',\n             learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4,\n             max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n             missing=nan, monotone_constraints='()', n_estimators=100,\n             n_jobs=-1, num_parallel_tree=1, predictor='auto', random_state=112,\n             reg_alpha=0, reg_lambda=1, ...)</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>catboost</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"323e24e9-7362-4d9e-a790-a57a0ac77961\" type=\"checkbox\" ><label class=\"sk-toggleable__label\" for=\"323e24e9-7362-4d9e-a790-a57a0ac77961\">CatBoostRegressor</label><div class=\"sk-toggleable__content\"><pre><catboost.core.CatBoostRegressor object at 0x7f9a07d5fc50></pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>lightgbm</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"ff7073e4-69ab-4a1f-8f33-6234aff89dc6\" type=\"checkbox\" ><label class=\"sk-toggleable__label\" for=\"ff7073e4-69ab-4a1f-8f33-6234aff89dc6\">LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(device='gpu', random_state=112)</pre></div></div></div></div></div></div></div></div></div></div>"},"metadata":{}}]},{"cell_type":"markdown","source":"### Model Residual Plot","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize = (10,10))\nplot_model(final, plot = 'residuals')","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:10:15.533804Z","iopub.execute_input":"2022-10-10T14:10:15.534165Z","iopub.status.idle":"2022-10-10T14:10:40.739642Z","shell.execute_reply.started":"2022-10-10T14:10:15.534136Z","shell.execute_reply":"2022-10-10T14:10:40.738682Z"},"trusted":true},"execution_count":32,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x720 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"### Error plot","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize = (10,10))\nplot_model(final, plot = 'error')","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:10:55.954276Z","iopub.execute_input":"2022-10-10T14:10:55.954887Z","iopub.status.idle":"2022-10-10T14:11:04.365894Z","shell.execute_reply.started":"2022-10-10T14:10:55.954851Z","shell.execute_reply":"2022-10-10T14:11:04.364945Z"},"trusted":true},"execution_count":33,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x720 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"### Xgboost model feature importance plot","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize = (10,10));\nplot_model(final.named_estimators_[list(final.named_estimators)[0]], plot = 'feature');","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:11:11.719334Z","iopub.execute_input":"2022-10-10T14:11:11.720399Z","iopub.status.idle":"2022-10-10T14:11:12.464839Z","shell.execute_reply.started":"2022-10-10T14:11:11.720359Z","shell.execute_reply":"2022-10-10T14:11:12.463809Z"},"trusted":true},"execution_count":34,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x720 with 0 Axes>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 800x500 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"### SHAP feature importance plot","metadata":{}},{"cell_type":"code","source":"interpret_model(final.named_estimators_[list(final.named_estimators)[0]])","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:11:34.925117Z","iopub.execute_input":"2022-10-10T14:11:34.925801Z","iopub.status.idle":"2022-10-10T14:12:13.485187Z","shell.execute_reply.started":"2022-10-10T14:11:34.925764Z","shell.execute_reply":"2022-10-10T14:12:13.484195Z"},"trusted":true},"execution_count":35,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 576x684 with 2 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"### Apply the pre-processing steps to test data","metadata":{}},{"cell_type":"code","source":"test=pre_process(test)","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:34:05.076655Z","iopub.execute_input":"2022-10-10T14:34:05.077985Z","iopub.status.idle":"2022-10-10T14:34:14.597491Z","shell.execute_reply.started":"2022-10-10T14:34:05.077942Z","shell.execute_reply":"2022-10-10T14:34:14.596493Z"},"trusted":true},"execution_count":38,"outputs":[]},{"cell_type":"markdown","source":"### Predict the new data","metadata":{}},{"cell_type":"code","source":"test['Target']=(predict_model(final, data=test.loc[:,X.columns])['Label'])","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:34:19.143144Z","iopub.execute_input":"2022-10-10T14:34:19.143828Z","iopub.status.idle":"2022-10-10T14:34:28.090008Z","shell.execute_reply.started":"2022-10-10T14:34:19.143791Z","shell.execute_reply":"2022-10-10T14:34:28.089000Z"},"trusted":true},"execution_count":39,"outputs":[]},{"cell_type":"markdown","source":"### Rotor bearing temperature of train and test data","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(6,4))\nplt.hist(train['target'],label='Train');\nplt.hist(test['Target'],label='Test');\nplt.legend();","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:37:25.252781Z","iopub.execute_input":"2022-10-10T14:37:25.253138Z","iopub.status.idle":"2022-10-10T14:37:25.572233Z","shell.execute_reply.started":"2022-10-10T14:37:25.253108Z","shell.execute_reply":"2022-10-10T14:37:25.571228Z"},"trusted":true},"execution_count":48,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"### Create result dataframe","metadata":{}},{"cell_type":"code","source":"res=pd.DataFrame({'Target':test['Target']})","metadata":{"execution":{"iopub.status.busy":"2022-10-10T14:34:30.593164Z","iopub.execute_input":"2022-10-10T14:34:30.593906Z","iopub.status.idle":"2022-10-10T14:34:30.600157Z","shell.execute_reply.started":"2022-10-10T14:34:30.593862Z","shell.execute_reply":"2022-10-10T14:34:30.598917Z"},"trusted":true},"execution_count":40,"outputs":[]},{"cell_type":"markdown","source":"### Write the dataframe to csv","metadata":{}},{"cell_type":"code","source":"res.to_csv(\"pycaret_blend.csv\",index=False)","metadata":{"execution":{"iopub.status.busy":"2022-08-30T13:19:16.446935Z","iopub.execute_input":"2022-08-30T13:19:16.447769Z","iopub.status.idle":"2022-08-30T13:19:16.990803Z","shell.execute_reply.started":"2022-08-30T13:19:16.447729Z","shell.execute_reply":"2022-08-30T13:19:16.989731Z"},"trusted":true},"execution_count":20,"outputs":[]}]}