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AutoViML /featurewiz

Star630

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

feature-selection feature-extraction xgboost feature-engineering autoencoders categorical-variables mrmr rfe featuretools rfecv feature-encoding best-encoders feature-engg

UpdatedFeb 19, 2025
Python

Hameem1 /Step-Detection-using-Machine-Learning

Star17

Implements an entire machine learning pipeline to train and evaluate a Random Forest Classifier on labeled gait data for walking. Data generated during the experiment has led to helpful insights in to the problem domain.

python machine-learning random-forest scikit-learn data-visualization feature-selection feature-extraction classification supervised-machine-learning model-training step-detection gait-analysis rfe rfecv data-pre-processing step-counting model-testing

UpdatedDec 8, 2022
Python

nalron /project_credit_scoring_model

Star5

Développer un modèle de scoring de la probabilité de défaut de paiement du client pour étayer la décision d'accorder ou non un prêt à un client potentiel.

python dashboard hyperopt banking-applications heroku-deployment scoring-models rfecv lightgbm-classifier nalron-beta

UpdatedMay 22, 2021
Jupyter Notebook

RuiFSP /mlzoomcamp2024-midterm-project

Star2

Midterm project for mlzoomcamp 2024

docker dockerfile aws machine-learning python3 xgboost elasticbeanstalk pipenv rfecv streamlit xgboost-classifier

UpdatedNov 23, 2024
Jupyter Notebook

mohd-faizy /feature-engineering-hacks

Star2

This repository contains a collection of hacks and tips for feature engineering. It is a great resource for anyone who wants to learn how to improve the performance of their machine learning models.

data-science machine-learning feature-selection feature-extraction feature-engineering rfe rfecv chi2

UpdatedJul 2, 2024
Jupyter Notebook

junayed-hasan /occupational-stress-ml

Star1

This repository contains code, datasets, and analysis for AI-driven occupational stress detection using machine learning, deep learning, and NLP. It includes feature selection, explainable AI, synthetic data generation, and model validation for workplace safety applications. 🚀

machine-learning exploratory-data-analysis cross-validation anova synthetic-dataset-generation deployment-automation explainable-ai rfecv huggingface large-language-models

UpdatedMar 15, 2025
Jupyter Notebook

rakibhhridoy /MachineLearning-FeatureSelection

Star1

Before training a model or feed a model, first priority is on data,not in model. The more data is preprocessed and engineered the more model will learn. Feature selectio one of the methods processing data before feeding the model. Various feature selection techniques is shown here.

machine-learning numpy scikit-learn pandas feature-selection pca logistic-regression lasso-regression gridsearchcv rfe rfecv selectkbest extratreesclassifier

UpdatedAug 18, 2020
Python

attilalr /RFE-cross-validation

Star1

RFE (Recursive Feature Elimination) with cross-validation

machine-learning feature-selection rfecv

UpdatedDec 1, 2022
Python

KevinAbrahamRepo /Data-Analytics-Projects

Star1

Big data manipulation and modelling projects

nlp text-mining numpy scikit-learn text-analysis nltk matplotlib tableau feature-engineering powerbi principal-component-analysis clustering-algorithm tokenization imbalanced-data smote classification-algorithm stemming-algorithm imbalanced-learning tweepy-api rfecv

UpdatedNov 3, 2019
Jupyter Notebook

gitakartika /antioxidant-protein-classification

Star1

Classify antioxidant property on protein sequence based on protein sequence feature

svm feature-selection feature-extraction hyperparameter-optimization classification protein-sequences hyperparameter-tuning rfecv

UpdatedMay 22, 2020
Jupyter Notebook

SitanshuA091 /Churn-Prediction

Star0

Churn Prediction Web Application for streamlit

machine-learning xgboost smote rfecv streamlit

UpdatedMay 5, 2024
Jupyter Notebook

yerartdev /tfm-pb

Star0

Trabajo fin de máster de ciencia de datos UC-UIMP-CSIC 2018-2019

r scikit-learn python3 feature-selection auc binary-classification imbalanced-data notebook-jupyter chisquare-test rfe rfecv filter-methods wrapper-methods embedded-methods

UpdatedAug 12, 2020
Jupyter Notebook

DataScienceVishal /Bank_Customer_Behaviour

Star0

Bank Customer Behaviour Prediction

cross-validation logistic-regression minmaxscaling rfe rfecv randomizedsearchcv dummy-variables-encoding

UpdatedMar 20, 2024
Jupyter Notebook

kumaranurag7 /Retail-Price-Analysis-and-Prediction

Star0

We have a data of retail transactions over two year. Apart from data analysis and visualization, a regression model is developed to predict the price of retail items belonging to different categories. Foretelling the Retail price can be a daunting task due to the huge datasets with a variety of attributes ranging from Text, Numbers(floats, integ…

python scikit-learn pandas boosting xgboost-algorithm rfecv

UpdatedMar 1, 2022
Jupyter Notebook

hanfei1986 /Random-forest-and-RFECV

Star0

This Jupyter notebook demonstrates a Recursive Feature Elimination with Cross-Validation (RFECV) feature selection process with a random forest model.

machine-learning random-forest rfecv

UpdatedAug 27, 2023
Jupyter Notebook

Upendra-Allagadda /Diabetes-prediction-using-machine-learning

Star0

Hospitals contain large databases. We can use that data to discover new useful and potentially life saving knowledge. Here we use datamining especially to predict type 2 diabetes mellitus.Predicting the percentage of chance of occurrence of Diabetes mellitus type 2 with less time complexity and high accuracy.

machine-learning random-forest ml python3 naive-bayes-classifier kmeans kmeans-clustering diabetes-prediction rfe rfecv