Feature engineering package with sklearn like functionality

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.

Leave One Feature Out Importance

EvalML is an AutoML library written in python.

Features selector based on the self selected-algorithm, loss function and validation method

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.

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

Easy to use Python library of customized functions for cleaning and analyzing data.

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

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

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

Feature Selection using Genetic Algorithm (DEAP Framework)

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

ML hyperparameters tuning and features selection, using evolutionary algorithms.

Awesome Domain Adaptation Python Toolbox

This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.

zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

A Machine Learning Approach of Emotional Model

A fast xgboost feature selection algorithm

scikit-learn compatible implementation of stability selection.