Optimal-Feature-selection-for-KNN-classifier

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

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This work implements the KNN classifier to train and classify the medical disease datasets like Breast cancer, Heart rate, Lomography data, etc. To improve the classification accuracy and reduce computational overhead, we proposed the hybrid optimization algorithm to optimally select the features from the database. The present repository has the MATLAB code for feature selection GoA and SA only. Read more here

https://free-thesis.com/product/feature-selection-and-classification-by-hybrid-optimization/

Cite As

Abhishek Gupta (2026). Optimal-Feature-selection-for-KNN-classifier (https://github.com/earthat/Optimal-Feature-selection-for-KNN-classifier), GitHub. Retrieved .

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes Action
1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.