This MATLAB code implements the binary Grass hopper optimization algorithm to select the features and train with KNN
https://free-thesis.com/product/feature-selection-and-classification-by-hybrid-optimization/
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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
- Version 1.0.0 (152 KB)
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View License on GitHub
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 |
