Uses of Interface
smile.math.distance.Metric

Packages that use Metric

Package	Description
smile.math.distance	Distance and metric measures.

Uses of Metric in smile.math.distance

Classes in smile.math.distance that implement Metric

Modifier and Type	Class and Description
class	ChebyshevDistance Chebyshev distance (or Tchebychev distance), or L∞ metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.
class	EditDistance The Edit distance between two strings is a metric for measuring the amount of difference between two sequences.
class	EuclideanDistance Euclidean distance.
class	HammingDistance<T> In information theory, the Hamming distance between two strings of equal length is the number of positions for which the corresponding symbols are different.
class	JensenShannonDistance The Jensen-Shannon divergence is a popular method of measuring the similarity between two probability distributions.
class	LeeDistance In coding theory, the Lee distance is a distance between two strings x1x2...xn and y1y2...yn of equal length n over the q-ary alphabet {0,1,...,q-1} of size q ≥ 2, defined as
class	MahalanobisDistance In statistics, Mahalanobis distance is based on correlations between variables by which different patterns can be identified and analyzed.
class	ManhattanDistance Manhattan distance, also known as L1 distance or L1 norm, is the sum of the (absolute) differences of their coordinates.
class	MinkowskiDistance Minkowski distance of order p or Lp-norm, is a generalization of Euclidean distance that is actually L2-norm.
class	SparseChebyshevDistance Chebyshev distance (or Tchebychev distance), or L∞ metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.
class	SparseEuclideanDistance Euclidean distance.
class	SparseManhattanDistance Manhattan distance, also known as L1 distance or L1 norm, is the sum of the (absolute) differences of their coordinates.
class	SparseMinkowskiDistance Minkowski distance of order p or Lp-norm, is a generalization of Euclidean distance that is actually L2-norm.