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Accord.Math.Distances Namespace

Public classBhattacharyya
Bhattacharyya distance.
Public classLogLikelihoodT
Log-likelihood distance between a sample and a statistical distribution.
Public classMahalanobis
Mahalanobis distance.
Public classMinkowski
The Minkowski distance is a metric in a normed vector space which can be considered as a generalization of both the Euclidean distance and the Manhattan distance.
Public classModular
Modular distance (shortest distance between two marks on a circle).
Public classSquareMahalanobis
Squared Mahalanobis distance.
Public structureAngular
Angular distance, or the proper distance metric version of Cosine distance.
Public structureArgMax
ArgMax distance (L0) distance.
Public structureBrayCurtis
Bray-Curtis distance.
Public structureCanberra
Canberra distance.
Public structureChebyshev
Chebyshev distance.
Public structureCosine
Cosine distance. For a proper distance metric, see Angular.
Public structureDice
Dice dissimilarity.
Public structureEuclidean
Euclidean distance metric.
Public structureHamming
Hamming distance.
Public structureHammingT
Hamming distance.
Public structureHellinger
Herlinger distance.
Public structureJaccard
Jaccard (Index) distance.
Public structureJaccardT
Jaccard (Index) distance.
Public structureKulczynski
Kulczynski dissimilarity.
Public structureLevenshtein
Levenshtein distance.
Public structureLevenshteinT
Levenshtein distance.
Public structureManhattan
Manhattan (also known as Taxicab or L1) distance.
Public structureMatching
Matching dissimilarity.
Public structurePearsonCorrelation
Pearson Correlation similarity.
Public structureRogersTanimoto
Rogers-Tanimoto dissimilarity.
Public structureRusselRao
Russel-Rao dissimilarity.
Public structureSokalMichener
Sokal-Michener dissimilarity.
Public structureSokalSneath
Sokal-Sneath dissimilarity.
Public structureSquareEuclidean
Square-Euclidean distance and similarity. Please note that this distance is not a metric as it doesn't obey the triangle inequality.
Public structureYule
Yule dissimilarity.