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 Mahalanobis distance first …

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 anomaly 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 is a powerful statistical tool that provides a robust measure of distance in multivariate data analysis. Its ability to account for correlations and variances within the data makes it …

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 deviation units …

Dec 23, 2024 · This can be useful when the features are correlated, as the Mahalanobis distance takes correlation into account. In particular, it can be useful for anomaly detection, since an anomaly by …

Mahalanobis distance is widely used in cluster analysis and classification techniques. It is closely related to Hotelling's T-square distribution used for multivariate statistical testing and Fisher's linear …