Distance and clustering.

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hello_world 2016-8-13

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评论： John D'Errico 2016-8-13

In k-means clustering code which uses Euclidean distance. I want to replace Euclidean distance by Mahalanobis distance.

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Answer 1

Image Analyst 2016-8-13

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Can you program in the formula from here: https://en.wikipedia.org/wiki/Mahalanobis_distance

Or just use the mahal() function if you have the Statistics and Machine Learning Toolbox:

Description d = mahal(Y,X) computes the Mahalanobis distance (in squared units) of each observation in Y from the reference sample in matrix X. If Y is n-by-m, where n is the number of observations and m is the dimension of the data, d is n-by-1. X and Y must have the same number of columns, but can have different numbers of rows. X must have more rows than columns.