Module: neurospin.clustering.clustering
Clustering routines.
Author: Bertrand Thirion (INRIA Saclay, Orsay, France), 2004-2008.
-
nipy.neurospin.clustering.clustering.kmeans(X, nbclusters=2, Labels=None, maxiter=300, delta=0.0001, verbose=0)
- Centers, Labels, J = Cmeans(X,nbclusters,Labels,maxiter,delta)
- cmeans clustering algorithm
INPUT :
- A data array X, supposed to be written as (n*p)
where n = number of features, p =number of dimensions
- nbclusters (int), the number of desired clusters
- Labels=None n array of predefined Labels.
if None or inadequate a random initilization is performed.
- maxiter(int, =300 by default), the maximum number
of iterations before convergence
- delta(double, =0.0001 by default),
the relative increment in the results before declaring convergence
- verbose=0: verboseity mode
OUPUT :
- Centers: array of size nbclusters*p, the centroids of
the resulting clusters
- Labels : arroy of size n, the discrete labels of the input items;
- J the final value of the criterion