Kernel Kmeans

kernel kmeans algorithm

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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 .

Categories

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General Information

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()
Improve the code and fix a bug of returning energy
update description

1.6.0.0

n/a

1.5.0.0

fix a minor bug of returning energy

1.2.0.0

remove empty clusters

1.1.0.0

add sample data and detail description

1.0.0.0