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).
Citar como
Mo Chen (2024). Kernel Kmeans (https://www.mathworks.com/matlabcentral/fileexchange/26182-kernel-kmeans), MATLAB Central File Exchange. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxCategorías
Etiquetas
Agradecimientos
Inspirado por: Pattern Recognition and Machine Learning Toolbox, Kmeans Clustering
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knkmeans/
Versión | Publicado | Notas de la versión | |
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1.8.0.0 | tweak |
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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 |
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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 |