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.

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 …

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

P.C. Mahalanobis, Indian statistician who devised the Mahalanobis distance and was instrumental in formulating India’s strategy for industrialization in the Second Five-Year Plan (1956–61).

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 measures the distance of a point x from a data distribution. The data distribution is characterized by a mean and the covariance matrix, thus is hypothesized as a …

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 …

Mahalanobis distance is a statistical measure used to determine the similarity between two data points in a multidimensional space. It is instrumental in data analysis, pattern recognition, and …

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, …