Uses of Interface
elki.distance.Norm

Packages that use Norm

Package	Description
elki.datasource.filter.normalization.instancewise	Instancewise normalization, where each instance is normalized independently.
elki.distance	Distance functions for use within ELKI.
elki.distance.colorhistogram	Distance functions for color histograms.
elki.distance.minkowski	Minkowski space Lp norms such as the popular Euclidean and Manhattan distances.
elki.distance.subspace	Distance functions based on subspaces.

Uses of Norm in elki.datasource.filter.normalization.instancewise

Fields in elki.datasource.filter.normalization.instancewise declared as Norm

Modifier and Type	Field	Description
(package private) Norm<? super V>	LengthNormalization.norm	Norm to use.
(package private) Norm<? super V>	LengthNormalization.Par.norm	Norm to use.

Constructors in elki.datasource.filter.normalization.instancewise with parameters of type Norm

Constructor	Description
LengthNormalization(Norm<? super V> norm)	Constructor.

Uses of Norm in elki.distance

Classes in elki.distance that implement Norm

Modifier and Type	Class	Description
class	MahalanobisDistance	Mahalanobis quadratic form distance for feature vectors.
class	MatrixWeightedQuadraticDistance	Matrix weighted quadratic distance, the squared form of MahalanobisDistance.

Uses of Norm in elki.distance.colorhistogram

Classes in elki.distance.colorhistogram that implement Norm

Modifier and Type	Class	Description
class	HSBHistogramQuadraticDistance	Distance function for HSB color histograms based on a quadratic form and color similarity.
class	RGBHistogramQuadraticDistance	Distance function for RGB color histograms based on a quadratic form and color similarity.

Uses of Norm in elki.distance.minkowski

Classes in elki.distance.minkowski that implement Norm

Modifier and Type	Class	Description
class	EuclideanDistance	Euclidean distance for NumberVectors.
class	LPIntegerNormDistance	Lp-Norm for NumberVectors, optimized version for integer values of p.
class	LPNormDistance	Lp-Norm (Minkowski norms) are a family of distances for NumberVectors.
class	ManhattanDistance	Manhattan distance for NumberVectors.
class	MaximumDistance	Maximum distance for NumberVectors.
class	MinimumDistance	Minimum distance for NumberVectors.
class	SparseEuclideanDistance	Euclidean distance function, optimized for SparseNumberVectors.
class	SparseLPNormDistance	Lp-Norm, optimized for SparseNumberVectors.
class	SparseManhattanDistance	Manhattan distance, optimized for SparseNumberVectors.
class	SparseMaximumDistance	Maximum distance, optimized for SparseNumberVectors.
class	SparseSquaredEuclideanDistance	Squared Euclidean distance function, optimized for SparseNumberVectors.
class	SquaredEuclideanDistance	Squared Euclidean distance, optimized for SparseNumberVectors.
class	WeightedEuclideanDistance	Weighted Euclidean distance for NumberVectors.
class	WeightedLPNormDistance	Weighted version of the Minkowski Lp norm distance for NumberVector.
class	WeightedManhattanDistance	Weighted version of the Manhattan (L1) metric.
class	WeightedMaximumDistance	Weighted version of the maximum distance function for NumberVectors.
class	WeightedSquaredEuclideanDistance	Weighted squared Euclidean distance for NumberVectors.

Uses of Norm in elki.distance.subspace

Classes in elki.distance.subspace that implement Norm

Modifier and Type	Class	Description
class	OnedimensionalDistance	Distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension only.
class	SubspaceEuclideanDistance	Euclidean distance function between NumberVectors only in specified dimensions.
class	SubspaceLPNormDistance	Lp-Norm distance function between NumberVectors only in specified dimensions.
class	SubspaceManhattanDistance	Manhattan distance function between NumberVectors only in specified dimensions.
class	SubspaceMaximumDistance	Maximum distance function between NumberVectors only in specified dimensions.