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Optimal-Feature-selection-for-KNN-classifier

version 1.0.0 (162 KB) by Abhishek Gupta
This MATLAB code implements the binary Grass hopper optimization algorithm to select the features and train with KNN

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Updated 05 Apr 2019

GitHub view license on GitHub

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 (2019). Optimal-Feature-selection-for-KNN-classifier (https://www.github.com/earthat/Optimal-Feature-selection-for-KNN-classifier), GitHub. Retrieved .

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Matlab

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