boruta_py

Feature selector

An implementation of a feature selection method to identify all relevant features for prediction

Python implementations of the Boruta all-relevant feature selection method.

GitHub

2k stars
41 watching
258 forks
Language: Python
last commit: 3 months ago
Linked from 2 awesome lists


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
jundongl/scikit-feature A collection of feature selection algorithms for machine learning in Python 1,509
epistasislab/scikit-rebate An implementation of Relief-based feature selection algorithms for Machine Learning. 409
chasedehan/boostaroota An algorithm for fast feature selection using XGBoost and other tree-based classifiers 219
craigacp/feast A software toolbox for feature selection algorithms 69
manuel-calzolari/sklearn-genetic A genetic feature selection tool for machine learning models 323
scikit-learn-contrib/skope-rules A Python machine learning module that generates logical rules to predict class labels with high precision 625
jaswinder9051998/zoofs A Python library that performs feature selection using various nature-inspired optimization algorithms. 243
scikit-learn/scikit-learn A comprehensive Python module for machine learning built on top of SciPy 60,136
lacava/few Automates feature engineering by using genetic programming to select the most useful features for machine learning models. 51
bodokaiser/piwise This project provides a Python implementation of various deep learning architectures for pixel-wise segmentation tasks. 383
feature-engine/feature_engine A Python library with multiple transformers to engineer and select features for use in machine learning models. 1,926
sjlu/popular-movies A tool that uses heuristics to generate a list of popular movies based on data from multiple sources. 371
sebp/scikit-survival A Python module for analyzing the time to an event in response to certain factors or covariates 1,135
yeolab/anchor An algorithm to identify unimodal, bimodal, and multimodal features in data 27
andosa/treeinterpreter Provides a way to decompose scikit-learn model predictions into bias and feature contribution components. 744