Uses of Interface
smile.math.distance.Distance

Packages that use Distance

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

Uses of Distance in smile.math.distance

Subinterfaces of Distance in smile.math.distance

Modifier and Type	Interface and Description
interface	Metric<T> A metric function defines a distance between elements of a set.

Classes in smile.math.distance that implement Distance

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	CorrelationDistance Correlation distance is defined as 1 - correlation coefficient.
class	DynamicTimeWarping<T> Dynamic time warping is an algorithm for measuring similarity between two sequences which may vary in time or speed.
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	JaccardDistance<T> The Jaccard index, also known as the Jaccard similarity coefficient is a statistic used for comparing the similarity and diversity of sample sets.
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.

Constructors in smile.math.distance with parameters of type Distance

Constructor and Description
DynamicTimeWarping(Distance<T> distance) Constructor.
DynamicTimeWarping(Distance<T> distance, double radius) Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.