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neurospin.clustering.bootstrap_hc

Module: neurospin.clustering.bootstrap_hc

This module provides some code to perform bootstrap of Ward’s hierarchical clustering This is useful to statistically validate clustering results. theory see:

Author : Bertrand Thirion, 2008

Functions

nipy.neurospin.clustering.bootstrap_hc.demo_ward_msb(n=30, d=30, niter=1000)
basic demo for the ward_msb procedure in that case the dominant split with 2 clusters should have dominant p-val INPUT: - n,d : the dimensions of the dataset -niter : the number of bootrstraps
nipy.neurospin.clustering.bootstrap_hc.ward_msb(X, niter=1000)
multi-scale bootstrap procedure INPUT: - X array of shape (n,p) where n is the number of items to be clustered p is their dimensions - niter=1000 number of iterations of the bootstrap OUPUT: - t the resulting tree clustering the associated subtrees is defined as t.list_of_subtrees() there are precisely n such subtrees - cpval: array of shape (n) : the corrected p-value of the clusters - upval: array of shape (n) : the uncorrected p-value of the clusters