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Feature Selection Python Packages

Python packages with the GitHub topic feature-selection. Sorted by relevance, with stars and monthly downloads.
feature-engine
feature-engine

Feature engineering and selection open-source Python library compatible with sklearn.

319K 2K 342
predict-idlab
powershap

A power-full Shapley feature selection method.

80K 215 24
smazzanti
mrmr-selection

mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.

65K 624 90
upgini
upgini

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

37K 349 26
abess-team
abess

Fast Best-Subset Selection Library

21K 483 43
EpistasisLab
skrebate

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

11K 421 72
alteryx
evalml

EvalML is an AutoML library written in python.

10K 848 93
AutoViML
featurewiz

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.

10K 678 99
ThomasBury
arfs

All Relevant Feature Selection

9K 143 15
gmrukwa
divik

Divisive Intelligent K-Means algorithm (DiviK) for joint feature selection and clustering of heavily multidimensional data.

8K 14 6
NVIDIA-Merlin
nvtabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

8K 1K 149
cerlymarco
shap-hypetune

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

7K 584 73
rodrigo-arenas
sklearn-genetic-opt

ML hyperparameters tuning and features selection, using evolutionary algorithms.

6K 361 91
scikit-learn-contrib
fastcan

A fast canonical-correlation-based search algorithm for feature selection, system identification, data pruning, etc.

5K 23 5
scottroberts140
dsr-feature-eng-ml

Machine learning model evaluation and feature engineering framework with hyperparameter tuning, data balancing, and feature importance analysis.

4K 1 0
runopti
stg

feature selection using stochastic gates

4K 111 24
Mamba413
ball

Statistical Inference and Sure Independence Screening via Ball Statistics

4K 31 1
konodyuk
kts

Interactive ML Toolset

3K 17 2
cod3licious
autofeat

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

3K 537 65
adapt-python
adapt

Awesome Domain Adaptation Python Toolbox

3K 371 55
kxytechnologies
kxy

A toolkit to boost the productivity of machine learning engineers.

3K 51 12
chasedehan
boostaroota

A fast xgboost feature selection algorithm

3K 234 36
aerdem4
lofo-importance

Leave One Feature Out Importance

3K 867 83
desbordante
desbordante

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

3K 478 100
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