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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Updated 5 Apr 2019

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 (2024). Optimal-Feature-selection-for-KNN-classifier (https://github.com/earthat/Optimal-Feature-selection-for-KNN-classifier), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
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.