I've been using Mahalanobis distance to look for outliers. This link: https://www.cs.princeton.edu/courses/archive/fall08/cos436/Duda/PR_Mahal/M_metric.htm says that feature scaling is addressed in the computation of the Mahalanobis distance. Am I interpreting this correctly?
1 Answer
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The Mahalanobis distance considers the variance of all the features while finding out the distance between two points, as is clear from the formula.
Feature scaling, generally, means that mean-centering and division by the standard deviation of the feature. If you scale all the feature and then find out the euclidean distance between two points, you will actually Mahalanobis distance.