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That is the foundation with the scree plot, during which you utilize eigenvalues to find out how many PCs you must retain to seize the bulk with the variance.
2) you Look at Every datapoint from matrix Y to each datapoint of matrix X, with, X the reference distribution (mu and sigma are calculated from X only)
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Reply Mercedes on December sixteen, 2020 3:35 am Thank you greatly Rick. This post and that of weblink the Cholesky transformation helped me greatly for any clustering I have been performing. I want to present a reference for your paper, and I used to be wondering if you could possibly suggest a reference of the publication to refer to for indicating that "The Euclidean distance calculated around the dataset Y is comparable to the Mahalanobis distance calculated in X." (Here, Y is the info scaled Using the inverse of your Cholesky transformation).
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