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

Packages that use Norm

Package	Description
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski	Minkowski space L_p norms such as the popular Euclidean and Manhattan distances.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.

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

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

Modifier and Type	Interface and Description
interface	DoubleNorm<O> Interface for norms in the double domain.

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

Modifier and Type	Class and Description
class	AbstractSpatialDoubleDistanceNorm Abstract base class for typical distance functions that allow rectangle-to-rectangle lower bounds.
class	AbstractVectorDoubleDistanceNorm Abstract base class for double-valued number-vector-based distances based on norms.
class	LorentzianDistanceFunction Lorentzian distance function for vector spaces.

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 Provides the Euclidean distance for FeatureVectors.
class	LPIntegerNormDistanceFunction Provides a LP-Norm for number vectors.
class	LPNormDistanceFunction Provides a LP-Norm for FeatureVectors.
class	ManhattanDistanceFunction Manhattan distance function to compute the Manhattan distance for a pair of FeatureVectors.
class	MaximumDistanceFunction Maximum distance function to compute the Maximum distance for a pair of FeatureVectors.
class	MinimumDistanceFunction Maximum distance function to compute the Minimum distance for a pair of FeatureVectors.
class	SparseEuclideanDistanceFunction Euclidean distance function.
class	SparseLPNormDistanceFunction Provides a LP-Norm for FeatureVectors.
class	SparseManhattanDistanceFunction Manhattan distance function.
class	SparseMaximumDistanceFunction Maximum distance function.
class	SquaredEuclideanDistanceFunction Provides the squared Euclidean distance for FeatureVectors.
class	WeightedEuclideanDistanceFunction Provides the Euclidean distance for FeatureVectors.
class	WeightedLPNormDistanceFunction Weighted version of the Minkowski L_p metrics distance function.
class	WeightedManhattanDistanceFunction Weighted version of the Minkowski L_p metrics distance function.
class	WeightedMaximumDistanceFunction Weighted version of the Minkowski L_p metrics distance function.
class	WeightedSquaredEuclideanDistanceFunction Provides the squared Euclidean distance for FeatureVectors.

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	DimensionSelectingDistanceFunction Provides a distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension.
class	SubspaceEuclideanDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.
class	SubspaceLPNormDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.
class	SubspaceManhattanDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.
class	SubspaceMaximumDistanceFunction Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.