Feature Selection

TPOTJupyter Notebook

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

MLxtendPython

A Python library providing extensions and utilities for data science and machine learning tasks.

SGX-Full-OrderBook-Tick-Data-Trading-StrategyJupyter Notebook

A machine learning framework for developing high-frequency trading strategies using full orderbook tick data.

Feature EnginePython

A Python library for feature engineering and selection with scikit-learn compatible transformers.

mlrR

A unified interface and infrastructure for machine learning in R, supporting classification, regression, clustering, and survival analysis.

boruta_pyPython

Python implementation of the Boruta all-relevant feature selection method with scikit-learn compatibility.

scikit-featurePython

An open-source Python repository providing around 40 feature selection algorithms for machine learning applications.

CloudForestGo

Fast, flexible, multi-threaded ensembles of decision trees for machine learning in pure Go.

Auto_ViMLPython

Automatically builds high-performance interpretable machine learning models with minimal features using a single line of code.

scikit-rebatePython

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

sklearn-genetic-optPython

Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.

zoofsPython

A Python library for feature selection using nature-inspired wrapper algorithms like particle swarm, grey wolf, and genetic optimization.

BoostARootaPython

A fast feature selection algorithm for tree-based models like XGBoost, designed to outperform Boruta in speed and performance.

visualize_MLPython

A Python package for automated univariate and bivariate data analysis and visualization to streamline machine learning workflows.

L2XPython

A method for selecting interpretable feature subsets from complex models using mutual information optimization.

GLMNetJulia

A Julia wrapper for fitting Lasso and ElasticNet GLM models using the glmnet Fortran library.

randomforestGo

A comprehensive Random Forest implementation in Go with extensions for deep forests, continuous learning, feature selection, and anomaly detection.

sk-transformerPython

A collection of pandas & scikit-learn compatible transformers for preprocessing and feature engineering 🛠