Efficient K-Means Clustering using JIT

Version 1.0.0.0 (2,02 KB) von Yi Cao
A simple but fast tool for K-means clustering
4.0
(11)
14,1K Downloads
Aktualisiert 16. Apr 2008

Lizenz anzeigen

This is a tool for K-means clustering. After trying several different ways to program, I got the conclusion that using simple loops to perform distance calculation and comparison is most efficient and accurate because of the JIT acceleration in MATLAB.

The code is very simple and well documented, hence is suitable for beginners to learn k-means clustering algorithm.

Numerical comparisons show that this tool could be several times faster than kmeans in Statistics Toolbox.

Zitieren als

Yi Cao (2024). Efficient K-Means Clustering using JIT (https://www.mathworks.com/matlabcentral/fileexchange/19344-efficient-k-means-clustering-using-jit), MATLAB Central File Exchange. Abgerufen.

Kompatibilität der MATLAB-Version
Erstellt mit R2007b
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux
Kategorien
Mehr zu Statistics and Machine Learning Toolbox finden Sie in Help Center und MATLAB Answers
Quellenangaben

Inspiriert: Patch color selector

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Version Veröffentlicht Versionshinweise
1.0.0.0

correct bugs in examples