This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.

Infinite Feature Selection: a Graph-based Feature Filtering Approach

Demonstration on how binary grey wolf optimization (BGWO) applied in the feature selection task.

Code of the paper：A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection --[Knowledge-Based Systems 22]

MatLab implementation of W-QEISS, F-QEISS and W-MOSS: three algorithms for the selection of (quasi) equally informative subsets

Intrusion Detection is a technique to identify the abnormal behavior of system due to attack. The unusual behavior of the environment is then identified and steps are taken and methods are formed to classify and recognize attacks. Data set containing a number of records sometimes may decrease the classifiers performance due to redundancy of data…

Application of Whale Optimization Algorithm (WOA) in the feature selection tasks.

Online Streaming Feature Selection

This collection of codes can be used for extracting features from continuous seismic signals for different machine learning tasks.

Simple, fast and ease of implementation. The filter feature selection methods include Relief-F, PCC, TV, and NCA.

Auto-UFSTool - An Automatic MATLAB Toolbox for Unsupervised Feature Selection

This repository integrates the codes for some feature selection & clustering methods.

Feature Selection by Optimized LASSO algorithm

A system to recognize hand gestures by applying feature extraction, feature selection (PCA) and classification (SVM, decision tree, Neural Network) on the raw data captured by the sensors while performing the gestures.

Code for paper "Autoencoder Inspired Unsupervised Feature Selection"

MATLAB code for Unsupervised Feature Selection with Multi-Subspace Randomization and Collaboration (SRCFS) (KBS 2019)

The binary version of Harris Hawk Optimization (HHO), called Binary Harris Hawk Optimization (BHHO) is applied for feature selection tasks.

Implantation of ant colony optimization (ACO) without predetermined number of selected features in feature selection tasks.

This MATLAB code implements the binary Grass hopper optimization algorithm to select the features and train with KNN

The binary version of Differential Evolution (DE), named as Binary Differential Evolution (BDE) is applied for feature selection tasks.