wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual demkmean wolffd@0: wolffd@0: wolffd@0: wolffd@0:

demkmean wolffd@0:

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wolffd@0: Purpose wolffd@0:

wolffd@0: Demonstrate simple clustering model trained with K-means. wolffd@0: wolffd@0:

wolffd@0: Synopsis wolffd@0:

wolffd@0:

wolffd@0: demkmean

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wolffd@0: Description wolffd@0:

wolffd@0: The problem consists of data in a two-dimensional space. wolffd@0: The data is wolffd@0: drawn from three spherical Gaussian distributions with priors 0.3, wolffd@0: 0.5 and 0.2; centres (2, 3.5), (0, 0) and (0,2); and standard deviations wolffd@0: 0.2, 0.5 and 1.0. The first figure contains a wolffd@0: scatter plot of the data. The data is the same as in demgmm1. wolffd@0: wolffd@0:

A cluster model with three components is trained using the batch wolffd@0: K-means algorithm. The matrix of centres is printed after training. wolffd@0: The second wolffd@0: figure shows the data labelled with a colour derived from the corresponding wolffd@0: cluster wolffd@0: wolffd@0:

wolffd@0: See Also wolffd@0:

wolffd@0: dem2ddat, demgmm1, knn1, kmeans

wolffd@0: Pages: wolffd@0: Index wolffd@0:

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