Uses of Interface
de.lmu.ifi.dbs.elki.distance.distancefunction.Norm

Packages that use Norm

Package	Description
de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise	Instancewise normalization, where each instance is normalized independently.
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram	Distance functions using correlations
de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski	Minkowski space Lp norms such as the popular Euclidean and Manhattan distances.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces
de.lmu.ifi.dbs.elki.index.tree.spatial.kd	K-d-tree and variants

Uses of Norm in de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise

Fields in de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise declared as Norm

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

Constructors in de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise with parameters of type Norm

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

Uses of Norm in de.lmu.ifi.dbs.elki.distance.distancefunction

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction that implement Norm

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

Uses of Norm in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram that implement Norm

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

Uses of Norm in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski that implement Norm

Modifier and Type	Class and Description
class	EuclideanDistanceFunction Euclidean distance for NumberVectors.
class	LPIntegerNormDistanceFunction Lp-Norm for NumberVectors, optimized version for integer values of p.
class	LPNormDistanceFunction Lp-Norm (Minkowski norms) are a family of distances for NumberVectors.
class	ManhattanDistanceFunction Manhattan distance for NumberVectors.
class	MaximumDistanceFunction Maximum distance for NumberVectors.
class	MinimumDistanceFunction Minimum distance for NumberVectors.
class	SparseEuclideanDistanceFunction Euclidean distance function, optimized for SparseNumberVectors.
class	SparseLPNormDistanceFunction Lp-Norm, optimized for SparseNumberVectors.
class	SparseManhattanDistanceFunction Manhattan distance, optimized for SparseNumberVectors.
class	SparseMaximumDistanceFunction Maximum distance, optimized for SparseNumberVectors.
class	SparseSquaredEuclideanDistanceFunction Squared Euclidean distance function, optimized for SparseNumberVectors.
class	SquaredEuclideanDistanceFunction Squared Euclidean distance, optimized for SparseNumberVectors.
class	WeightedEuclideanDistanceFunction Weighted Euclidean distance for NumberVectors.
class	WeightedLPNormDistanceFunction Weighted version of the Minkowski Lp norm distance for NumberVector.
class	WeightedManhattanDistanceFunction Weighted version of the Manhattan (L1) metric.
class	WeightedMaximumDistanceFunction Weighted version of the maximum distance function for NumberVectors.
class	WeightedSquaredEuclideanDistanceFunction Weighted squared Euclidean distance for NumberVectors.

Uses of Norm in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace that implement Norm

Modifier and Type	Class and Description
class	OnedimensionalDistanceFunction Distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension only.
class	SubspaceEuclideanDistanceFunction Euclidean distance function between NumberVectors only in specified dimensions.
class	SubspaceLPNormDistanceFunction Lp-Norm distance function between NumberVectors only in specified dimensions.
class	SubspaceManhattanDistanceFunction Manhattan distance function between NumberVectors only in specified dimensions.
class	SubspaceMaximumDistanceFunction Maximum distance function between NumberVectors only in specified dimensions.

Uses of Norm in de.lmu.ifi.dbs.elki.index.tree.spatial.kd

Fields in de.lmu.ifi.dbs.elki.index.tree.spatial.kd declared as Norm

Modifier and Type	Field and Description
private Norm<? super O>	MinimalisticMemoryKDTree.KDTreeKNNQuery.norm Norm to use.
private Norm<? super O>	MinimalisticMemoryKDTree.KDTreeRangeQuery.norm Norm to use.
private Norm<? super O>	SmallMemoryKDTree.KDTreeKNNQuery.norm Norm to use.
private Norm<? super O>	SmallMemoryKDTree.KDTreeRangeQuery.norm Norm to use.

Constructors in de.lmu.ifi.dbs.elki.index.tree.spatial.kd with parameters of type Norm

Constructor and Description
KDTreeKNNQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.
KDTreeKNNQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.
KDTreeRangeQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.
KDTreeRangeQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.