Distance and clustering.
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In k-means clustering code which uses Euclidean distance. I want to replace Euclidean distance by Mahalanobis distance.
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Image Analyst
2016-8-13
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.
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John D'Errico
2016-8-13
hello_world has been asking the same question repeatedly. This is the 4th question I've seen from them on the exact same topic.
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