Mahalanobis distance is the distance between a point and a distribution, it's a measure of how many standard deviations away the point is from the mean the distribution.
where is the Mahalanobis distance of the point
from a distribution with mean
, and
is the covariance matrix.
It also can be defined as a dissimilarity measure between two random vectors and
of the same distribution with the covariance matrix
The Mahalanobis distance will reduce to the Euclidean distance when is the identity matrix, and become the standardized Euclidean distance when
is diagonal.
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