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python Programming Glossary: cdistmore efficient way to calculate distance in numpy? http://stackoverflow.com/questions/17527340/more-efficient-way-to-calculate-distance-in-numpy getR4 VVm VVs HHm HHs from scipy.spatial.distance import cdist t0 time.time precomputed_flat numpy.column_stack VVs.flatten.. numpy.column_stack VVm.flatten HHm.flatten R spdist.cdist precomputed_flat measured_flat 'sqeuclidean' #.T print R4 t.. getR5 VVm VVs HHm HHs from scipy.spatial.distance import cdist t0 time.time precomputed_flat numpy.column_stack VVs.flatten..
Is it possible to specify your own distance function using Scikits.Learn K-Means Clustering? http://stackoverflow.com/questions/5529625/is-it-possible-to-specify-your-own-distance-function-using-scikits-learn-k-means import numpy as np from scipy.spatial.distance import cdist # scipy spatial distance.py # http docs.scipy.org doc scipy.. sparse csr.py __date__ 2011 11 17 Nov denis # X sparse any cdist metric real app # centres get dense rapidly metrics in high.. e.g. Lqmetric below p for minkowski metric local mod cdist for 0 p 1 too verbose 0 silent 2 prints running distances out..
Calculating the percentage of variance measure for k-means? http://stackoverflow.com/questions/6645895/calculating-the-percentage-of-variance-measure-for-k-means used EDIT 2 Distortion from scipy.spatial.distance import cdist D cdist points centroids 'euclidean' sum numpy.min D axis 1.. 2 Distortion from scipy.spatial.distance import cdist D cdist points centroids 'euclidean' sum numpy.min D axis 1 The output.. 6 7 1 2 1.1330618877807475 centroids numpy.array 6 7 1 2 D cdist points centroids 'euclidean' sum numpy.min D axis 1 9.0644951022459797..
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