In statistics, Mahalanobis distance is a distance measure introduced by P. C. Mahalanobis in 1936. It is based on correlations between variables by which different patterns can be identified and analyzed. It gauges similarity of an unknown sample set to a known one. It differs from Euclidean distance in that it takes into account the correlations of the data set and is scale-invariant. In other words, it is a multivariate effect size.
Read more about Mahalanobis Distance: Definition, Intuitive Explanation, Relationship To Leverage, Applications
Famous quotes containing the word distance:
“A solitary traveler whom we saw perambulating in the distance loomed like a giant. He appeared to walk slouchingly, as if held up from above by straps under his shoulders, as much as supported by the plain below. Men and boys would have appeared alike at a little distance, there being no object by which to measure them. Indeed, to an inlander, the Cape landscape is a constant mirage.”
—Henry David Thoreau (1817–1862)