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Anello92 / Machine_Learning_Python

Top Machine Learning Algorithms Detailed in Python and Preprocessing for Machine Learning

python machine-learning tree algorithm random-forest naive-bayes regression classification adaboost preprocessing knn ensemble-machine-learning extremely-randomized-trees bagging-ensemble

Updated Jul 13, 2021
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alifrmf / Mobile-Price-Prediction-Classification-Analysis

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Supervised Machine Learning Analysis Using Classification Models

Updated Jul 10, 2023
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jddeguia / bagging-lstm

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Implementation of bagging-based ensemble for solar irradiance prediction. Base learners used in ensemble learning is stacked-LSTM

python lstm forecasting pca solar smart-grid bagging-ensemble

Updated Aug 28, 2020
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somjit101 / Facebook-Friend-Recommendation

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This is a friend recommendation systems which are used on social media platforms (e.g. Facebook, Instagram, Twitter) to suggest friends/new connections based on common interests, workplace, common friends etc. using Graph Mining techniques. Here, we are given a social graph, i.e. a graph structure where nodes are individuals on social media plat…

machine-learning graph graph-algorithms social-network cross-validation xgboost graph-theory decision-trees social-network-analysis decision-tree-classifier gradient-boosting graph-similarity randomizedsearchcv bagging-ensemble boosting-ensemble facebook-friend-recommendation

Updated Feb 15, 2024
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bupt-ai-cz / BreastCancerCNN

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https://teacher.bupt.edu.cn/zhuchuang/en/index.htm

deep-neural-networks cnn model-compression breast-cancer-classification breakhist-dataset histopathology-images bagging-ensemble

Updated Jun 11, 2021
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rochitasundar / Customer-profiling-using-ML-EasyVisa

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The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidate…

decision-tree-classifier gradient-boosting-classifier f1-score random-forest-classifier grid-search-hyperparameters precision-recall accuracy-metrics xgboost-classifier stacking-ensemble adaboostclassifier bagging-ensemble grid-search-cross-validation

Updated Jan 20, 2022
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a3X3k / Spam-Email-Detection

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QuyAnh2005 / homemade-machine-learning

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Understand and code some basic algorithms in machine learning from scratch

python machine-learning algorithms random-forest naive-bayes linear-regression scikit-learn machine-learning-algorithms pca logistic-regression support-vector-machine theory decision-tree gradient-boosting k-means-clustering random-forest-algorithm implementation-from-scratch bagging-ensemble boosting-ensemble

Updated Mar 29, 2023
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itsmethahseer / clustering-and-Ensemble-techniques

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Welcome to the Machine Learning Repository - Part 4! This repository focuses on unsupervised machine learning algorithms, particularly clustering techniques, and explores the fascinating world of ensemble methods, including boosting and bagging.

machine-learning clustering scikit-learn pandas python3 boosting-algorithms modelbuilding bagging-ensemble

Updated Jul 26, 2023
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Erdos1729 / text-classification-ml

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Application of various text classification algorithms on multiple datasets.

machine-learning random-forest text-classification regex machine-learning-algorithms jupyter-notebook regular-expression text-processing decision-tree gradient-boosting knn-classification rocchio-algorithm linearsvc seaborn-plots bagging-ensemble nearest-centroid

Updated Oct 1, 2020
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Pythondeveloper6 / Ensemble-learning-beginner-guide

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machine learning ensemble learning types in easy steps with examples

machine-learning random-forest numpy ensemble-learning logistic-regression decision-trees svc knn-classification voting-classifier stacking-ensemble bagging-ensemble

Updated Jul 30, 2023
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prneidhardt / Ensemble-Learning

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EasyVisa Project

stacking-ensemble bagging-ensemble boosting-ensemble

Updated Nov 11, 2024
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Ayda-Darvishan / Tuning-ML-Classifiers

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The project includes building seven different machine learning classifiers (including Linear Regression, Decision Tree, Bagging, Random Forest, Gradient Boost, AdaBoost, and XGBoost) using Original, OverSampled, and Undersampled data of ReneWind case study, tuning hyperparameters of the models, performance comparisons, and pipeline development f…

pipeline random-forest exploratory-data-analysis cross-validation supervised-learning xgboost adaboost tuning-parameters gradient-boosting oversampling undersampling gridsearchcv randomizedsearchcv bagging-ensemble boosting-ensemble

Updated May 9, 2023
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daiphuongngo / Banking-Dataset-Imbalanced-Learn-Comparison

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Banking-Dataset-Marketing-Targets

machine-learning deep-neural-networks deep-learning random-forest tensorflow scikit-learn keras xgboost classification decision-tree balancedbaggingclassifier balanced-random-forest rusboost bagging-ensemble easyensembleclassifier

Updated Jul 31, 2022
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MoinDalvs / Assignment_Random_Forest_1

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Use Random Forest to prepare a model on fraud data treating those who have taxable income <= 30000 as "Risky" and others are "Good"

data-science hyperparameter-tuning random-forest-classifier bagging-trees bagging-ensemble

Updated Jun 5, 2022
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ligerfotis / CSE6363_Machine_Learning

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Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21