performs c-means clustering
[Centers] = CMeans(Samples, InitialCenters, NormType, Criterion, Value)
matrix that includes sample vectors as rows
matrix that includes initial cluster centers as rows
norm of vectors, must be a scalar greater than zeros, can be %inf
name of termination condition, can be 'iterations' or 'quantization_error'
number of iterations or maximum quantization error
resulting cluster centers
This function performs c-means clustering. For each row of Samples the nearest neighbor among InitialClusterCenters is searched. The new center of a cluster is the mean of its members.
The process terminates if the specified number of iterations is performed or the quantization error does not exceed a specified maximum.
If the termination condition is fullfilled from the beginning, Centers == InitialCenters
Richard O. Duda, Peter E. Hart, David G. Stork, 'Pattern Classification', John Wiley & Sons Inc., New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, Second Edition, 2001