Kernel Kmeans

kernel kmeans algorithm
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Aggiornato 11 mar 2017

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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).

Cita come

Mo Chen (2024). Kernel Kmeans (https://www.mathworks.com/matlabcentral/fileexchange/26182-kernel-kmeans), MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2016b
Compatibile con qualsiasi release
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Versione Pubblicato Note della release
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