Accord.Math.Distances Namespace 
Class  Description  

Bhattacharyya 
Bhattacharyya distance.
 
LogLikelihoodT 
Loglikelihood distance between a sample and a statistical distribution.

Structure  Description  

Angular 
Angular distance, or the proper distance metric version of Cosine distance.
 
ArgMax 
ArgMax distance (L0) distance.
 
BrayCurtis 
BrayCurtis distance.
 
Canberra 
Canberra distance.
 
Chebyshev 
Chebyshev distance.
 
Cosine 
Cosine distance. For a proper distance metric, see Angular.
 
Dice 
Dice dissimilarity.
 
DiracT 
Dirac distance.
 
Euclidean 
Euclidean distance metric.
 
Hamming 
Hamming distance.
 
HammingT 
Hamming distance.
 
Hellinger 
Herlinger distance.
 
Jaccard 
Jaccard (Index) distance.
 
JaccardT 
Jaccard (Index) distance.
 
Kulczynski 
Kulczynski dissimilarity.
 
Levenshtein 
Levenshtein distance.
 
LevenshteinT 
Levenshtein distance.
 
Mahalanobis 
Mahalanobis distance.
 
Manhattan 
Manhattan (also known as Taxicab or L1) distance.
 
Matching 
Matching dissimilarity.
 
Minkowski 
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.
 
Modular 
Modular distance (shortest distance between two marks on a circle).
 
PearsonCorrelation 
Pearson Correlation similarity.
 
RogersTanimoto 
RogersTanimoto dissimilarity.
 
RusselRao 
RusselRao dissimilarity.
 
SokalMichener 
SokalMichener dissimilarity.
 
SokalSneath 
SokalSneath dissimilarity.
 
SquareEuclidean 
SquareEuclidean distance and similarity. Please note that this
distance is not a metric as it doesn't obey the triangle inequality.
 
SquareMahalanobis 
Squared Mahalanobis distance.
 
WeightedEuclidean 
Weighted Euclidean distance metric.
 
WeightedSquareEuclidean 
Weighted SquareEuclidean distance and similarity. Please note that this
distance is not a metric as it doesn't obey the triangle inequality.
 
Yule 
Yule dissimilarity.

Interface  Description  

IDistance 
Common interface for distance functions (not necessarily metrics).
 
IDistanceT 
Common interface for distance functions (not necessarily metrics).
 
IDistanceT, U 
Common interface for distance functions (not necessarily metrics).
 
IMetricT 
Common interface for Metric distance functions.
 
ISimilarityT 
Common interface for similarity measures.
 
ISimilarityT, U 
Common interface for similarity measures.
