📊 Mahalanobis Distance Calculator
Compute multivariate distance while accounting for variable correlations.
Distance Calculator
Supports 2-D points for this demo.
For higher dimensions you’ll need a full matrix inversion algorithm.
σ₁₂ and σ₂₁ stay equal to keep Σ symmetric.
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About Mahalanobis
Mahalanobis distance measures how many standard deviations a point x is from the mean μ of a multivariate distribution, considering the covariance Σ.
Formula
d = √((x − μ)ᵀ Σ⁻¹ (x − μ))Typical Use-Cases
- • Multivariate outlier detection
- • Quality control (manufacturing)
- • Financial risk analysis
- • Pattern recognition
- • Cluster validation
When Σ is the identity matrix, Mahalanobis distance reduces to Euclidean distance.