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# lyngby_km_centersim

## (export/lyngby/lyngby_km_centersim.m)

### Function Synopsis

S = lyngby_km_centersim(X, Centers, assign, varargin)

### Help text

lyngby_km_centersim - K-means center similarity
function S = lyngby_km_centersim(X, Centers, assign)
Input: X Datamatrix, size: objects x variables
Centers Cluster centers, size: clusters x
variables
assign Assignment vector, size: objects x 1
Property: Similarity [ {InverseEuclidean} | corrcoef ]
Output: S Similarity matrix, size: objects x 1
This function will calculate the similarity between the
cluster centers and their assigned data points from the X
matrix.
If 'similarity' is 'InverseEuclidean' the similarity is
calculated as the inverse of the Euclidean distance:
1/sum( (X-center).^2 )
For 'CorrCoef' as 'similarity' the similarity is computed as
the correlation coefficient, that is between -1 and +1 as
implemented in the corrcoef Matlab function
See also LYNGBY, LYNGBY_KM_MAIN, LYNGBY_KM_PLOT_DIST.
$Id: lyngby_km_centersim.m,v 1.3 2003/01/30 12:03:20 fnielsen Exp $

### Cross-Reference Information

This function is called by

Produced by mat2html on Wed Jul 29 15:43:40 2009

Cross-Directory links are: OFF