Distance and clustering.
6 views (last 30 days)
Image Analyst on 13 Aug 2016
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.