som_kmeanscolor - clustering For clustering it uses...

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SOM Toolbox Online documentation som_kmeanscolor [color,best,kmeans]=som_kmeanscolor(sM,C,initRGB,contrast) SOM_KMEANSCOLOR Map unit color code according to K-means clustering color = som_kmeanscolor(sM, C, [initRGB], [contrast]) color = som_kmeanscolor(sM,15,som_colorcode(sM,'rgb1'),'enhance'); [color,best] = som_kmeanscolor(sM,15,[],'normal'); Input and output arguments ([]'s are optional): sM (struct) map struct C (scalar) maximum number of clusters initRGB (string, matrix) color code string accepted by SOM_COLORCODE or an Mx3 matrix of RGB triples, where M is the number of map units. Default: SOM_COLORCODEs default contrast (string) 'flat', 'enhanced' color contrast mode, default: 'enhanced' color (matrix) MxCx3 of RGB triples best (scalar) index for "best" clustering according to Davies-Boulding index; color(:,:,best) includes the corresponding color code. kmeans (cell) output of KMEANS_CLUSTERS in a cell array. The function gives a set of color codings according to K-means
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Unformatted text preview: clustering. For clustering, it uses function KMEANS_CLUSTERS for map units, and it calculates color codings for 1,2,. ..,C clusters. The idea of coloring is that the color of a cluster is the mean of the original colors (RGB values) of the map units belonging to that cluster, see SOM_CLUSTERCOLOR. The original colors are defined by SOM_COLORCODE by default. Input 'contrast' simply specifies whether or not to linearly redistribute R,G, and B values so that minimum is 0 and maximum 1 ('enahanced') or to use directly the output of SOM_CLUSTERCOLOR ('flat'). KMEANS_CLUSTERS uses certain heuristics to select the best of 5 trials for each number of clusters. Evaluating the clustering multiple times may take some time. EXAMPLE load iris; % or any other map struct sM [color,b]=som_kmeanscolor(sM,10); som_show(sM,'color',color,'color',{color(:,:,b),'"Best clustering"'); See also SOM_SHOW, SOM_COLORCODE, SOM_CLUSTERCOLOR, KMEANS_CLUSTERS [ SOM Toolbox online doc ]...
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This note was uploaded on 05/23/2010 for the course CS 245 taught by Professor Dunno during the Spring '10 term at Aarhus Universitet.

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