Jingwei Too

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.

JingweiToo

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.

JingweiToo

This toolbox offers 30 types of EEG feature extraction methods (HA, HM, HC, and etc.) for Electroencephalogram (EEG) applications.

JingweiToo

This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.

JingweiToo

This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, and etc., which are simpler and easy to implement.

JingweiToo

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

JingweiToo

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

JingweiToo

This toolbox offers advanced feature selection tools. Several modifications, variants, enhancements, or improvements of algorithms such as GWO, FPA, SCA, PSO and SSA are provided.

JingweiToo

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

JingweiToo