Recluster multilevel clustering to determine exactly K clusters
LABOUT = RECLUSTK(LABIN,K,LABREF)
| LABIN|| [M,L] array of indices for L clustering levels of M objects. Indices should point to the prototype objects of its cluster.|
| K|| Scalar or vector of length N with desired numbers of clusters. Default is a set of N clusterings between 2 and M/10 clusters. To reduce computing time small K's (eg K < 100) are recommended.|
| LABREF|| [M,1] vector of a high-resolution clustering to be used for estimating cluster distances. If omitted a high-resolution clustering from LABIN will be used.|
| LABOUT|| [M,N] array with the results of the multilevel clusterings of the|
| M|| objects. The columns refer to the N clusterings. They yield for the objects the prototype indices of the clusters they belong to.|
The multilevel clustering LABIN is used to find a set / sets of exactly K clusters. LABREF should be a set of)high-resolution clustering(s), obtaining many more clusters than demanded in K. It is used to estimate distances by CLUSTDIST between the clusters in a clustering in LABIN that has slightly more clusters than desired by K. In this clustering the clusters are combined using a single linkage procedure (DCLUSTH) based on the computed cluster distances.
This routine might be usefule for clustering procedures like CLUSTM and CLUSTS for which the number of desired clusters can not exactly be defined.
For large values of K this routine might be very time consuming.
datasets, mappings, dclusth, cluste, clustf, clustk, clusth, clustkh, clustm, reclusth, reclustn, testclust, clustcerr, clustc, clustnum, plotdg,
|This file has been automatically generated. If badly readable, use the help-command in Matlab.|