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This function performs kernel kmeans algorithm. When the linear kernel (i.e., inner product) is used, the algorithm is equivalent to standard kmeans algorithm. Several nonlinear kernel functions are also provided. Upon request, I also include a prediction function for out-of-sample inference. Please try following code for a demo:
clear; close all;
d = 2;
k = 3;
n = 500;
[X,label] = kmeansRnd(d,k,n);
init = ceil(k*rand(1,n));
[y,mse,model] = knKmeans(X,init,@knLin);
plotClass(X,y)
idx = 1:2:n;
Xt = X(:,idx);
t = knKmeansPred(model, Xt);
plotClass(Xt,t)
This function is now a part of the PRML toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox).
Cite As
Mo Chen (2026). Kernel Kmeans (https://au.mathworks.com/matlabcentral/fileexchange/26182-kernel-kmeans), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired by: Pattern Recognition and Machine Learning Toolbox, Kmeans Clustering
General Information
- Version 1.8.0.0 (4.1 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.8.0.0 | tweak |
||
| 1.7.0.0 | fix incompatibility issue due the stupid API change of function unique()
|
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| 1.6.0.0 | n/a |
||
| 1.5.0.0 | fix a minor bug of returning energy |
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| 1.2.0.0 | remove empty clusters |
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| 1.1.0.0 | add sample data and detail description |
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| 1.0.0.0 |
