The Mahalanobis distance is a measure of the distance between a point and a probability distribution , introduced by P. C. Mahalanobis in 1936. [1] The mathematical details of …

The Mahalanobis distance measures distance relative to the centroid — a base or central point which can be thought of as an overall mean for multivariate data.

May 14, 2025 · Explore comprehensive techniques to compute and interpret the Mahalanobis distance in multivariate analysis for reliable outlier detection.

Mahalanobis distance is an effective multivariate distance metric that measures the distance between a point (vector) and a distribution. It has excellent applications in multivariate …

P.C. Mahalanobis was an Indian statistician. He developed several practical mathematical and statistical methods—including the Mahalanobis distance—that he later applied to India’s social …

Mahalanobis distance is a multivariate distance metric that measures how far a point is from the center of a distribution, taking into account correlations between variables.

Mahalanobis distance is a more sophisticated measure than Euclidean distance for identifying outliers. While Euclidean distance simply calculates the straight-line distance between a point …

Named after Indian statistician Prasanta Chandra Mahalanobis, the method computes how far a point is from the mean of the distribution — not in terms of raw distance, but in standard …

Feb 15, 2012 · The Mahalanobis distance accounts for the variance of each variable and the covariance between variables. Geometrically, it does this by transforming the data into …

Prasanta Chandra Mahalanobis OBE, FNA, [5] FASc, [6] FRS [2] (29 June 1893 – 28 June 1972) was an Indian scientist and statistician. He is best remembered for the Mahalanobis distance, …