Optimal-Feature-selection-for-KNN-classifier

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

Zitieren als

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

Kompatibilität der MATLAB-Version
Erstellt mit R2019a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
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Versionen, die den GitHub-Standardzweig verwenden, können nicht heruntergeladen werden

Version Veröffentlicht Versionshinweise
1.0.0

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.
Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.