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📄 som_cllinkage.html

📁 Kohonen的SOM软件包
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<!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML//EN"><html><head><title>SOM Toolbox / som_cllinkage </title></head><body bgcolor=#f0f0f0><table border=0 width="100%" cellpadding=0 cellspacing=0><tr><td valign=baseline><font size=+2>SOM Toolbox</font></td><td valign=baseline align=center><a href="somtoolbox.html">Online documentation</td><td valign=baseline align=right><a href="http://www.cis.hut.fi/projects/somtoolbox/" target="_top">http://www.cis.hut.fi/projects/somtoolbox/</a></td></tr></table><hr><H1> som_cllinkage </H1><P><B> sC = som_cllinkage(sM,varargin)</B></P><PRE>SOM_CLLINKAGE Make a hierarchical linkage of the SOM map units. sC = som_cllinkage(sM, [[argID,] value, ...])    sC = som_cllinkage(sM);  sC = som_cllinkage(D,'complete');  sC = som_cllinkage(sM,'single','ignore',find(~som_hits(sM,D)));  sC = som_cllinkage(sM,pdist(sM.codebook,'mahal'));  som_clplot(sC);   Input and output arguments ([]'s are optional):   sM       (struct) map or data struct to be clustered            (matrix) size dlen x dim, a data set: the matrix must not                     contain any NaN's!   [argID,  (string) See below. The values which are unambiguous can     value]  (varies) be given without the preceeding argID.   sC       (struct) a clustering struct with e.g. the following fields                     (for more information see SOMCL_STRUCT)     .base  (vector) if base partitioning is given, this is a newly                      coded version of it so that the cluster indices                     go from 1 to the number of clusters.      .tree  (matrix) size clen-1 x 3, the linkage info                     Z(i,1) and Z(i,2) hold the indeces of clusters                      combined on level i (starting from bottom). The new                     cluster has index dlen+i. The initial cluster                      index of each unit is its linear index in the                      original data matrix. Z(i,3) is the distance                     between the combined clusters. See LINKAGE                     function in the Statistics Toolbox.      Here are the valid argument IDs and corresponding values. The values  which are unambiguous (marked with '*') can be given without the preceeding argID.   'topol'   *(struct) topology struct   'connect' *(string) 'neighbors' or 'any' (default), whether the                       connections should be allowed only between                        neighbors or between any vectors              (matrix) size dlen x dlen indicating the connections                       between vectors   'linkage' *(string) the linkage criteria to use: 'single' (the                       default), 'average', 'complete', 'centroid', or 'ward'    'dist'     (matrix) size dlen x dlen, pairwise distance matrix to                        be used instead of euclidian distances              (vector) as the output of PDIST function              (scalar) distance norm to use (default is euclidian = 2)   'mask'     (vector) size dim x 1, the search mask used to                        weight distance calculation. By default                        sM.mask or a vector of ones is used.   'base'     (vector) giving the base partitioning of the data:                        base(i) = j denotes that vector i belongs to                       base cluster j, and base(i) = NaN that vector                       i does not belong to any cluster, but should be                       ignored. At the beginning of the clustering, the                        vector of each cluster are averaged, and these                       averaged vectors are then clustered using                        hierarchical clustering.   'ignore'   (vector) units to be ignored (in addition to those listed                       in base argument)   'tracking' (scalar) 1 or 0: whether to show tracking bar or not (default = 0) Note that if 'connect'='neighbors' and some vector are ignored (as denoted by NaNs in the base vector), there may be areas on the map which will never be connected: connections across the ignored map units simply do not exist. In such a case, the neighborhood is gradually increased until  the areas can be connected. See also KMEANS_CLUSTERS, LINKAGE, PDIST, DENDROGRAM. </PRE><p><hr><br><center>[ <a href="somtoolbox.html">SOM Toolbox online doc</a> ]</center><br><!-- Last updated: May 30 2002 --></body></html>

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