Uses of Interface
org.apache.commons.math3.ml.distance.DistanceMeasure

Packages that use DistanceMeasure

Package	Description
org.apache.commons.math3.ml.clustering	Clustering algorithms.
org.apache.commons.math3.ml.clustering.evaluation	Cluster evaluation methods.
org.apache.commons.math3.ml.distance	Common distance measures.
org.apache.commons.math3.ml.neuralnet	Neural networks.
org.apache.commons.math3.ml.neuralnet.sofm	Self Organizing Feature Map.
org.apache.commons.math3.ml.neuralnet.twod.util	Utilities to visualize two-dimensional neural networks.

Uses of DistanceMeasure in org.apache.commons.math3.ml.clustering

Fields in org.apache.commons.math3.ml.clustering declared as DistanceMeasure

Modifier and Type	Field	Description
private DistanceMeasure	Clusterer.measure	The distance measure to use.

Methods in org.apache.commons.math3.ml.clustering that return DistanceMeasure

Modifier and Type	Method	Description
DistanceMeasure	Clusterer.getDistanceMeasure()	Returns the DistanceMeasure instance used by this clusterer.

Constructors in org.apache.commons.math3.ml.clustering with parameters of type DistanceMeasure

Constructor	Description
Clusterer(DistanceMeasure measure)	Build a new clusterer with the given DistanceMeasure.
DBSCANClusterer(double eps, int minPts, DistanceMeasure measure)	Creates a new instance of a DBSCANClusterer.
FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure)	Creates a new instance of a FuzzyKMeansClusterer.
FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure, double epsilon, RandomGenerator random)	Creates a new instance of a FuzzyKMeansClusterer.
KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure)	Build a clusterer.
KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, RandomGenerator random)	Build a clusterer.
KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, RandomGenerator random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)	Build a clusterer.

Uses of DistanceMeasure in org.apache.commons.math3.ml.clustering.evaluation

Fields in org.apache.commons.math3.ml.clustering.evaluation declared as DistanceMeasure

Modifier and Type	Field	Description
private DistanceMeasure	ClusterEvaluator.measure	The distance measure to use when evaluating the cluster.

Constructors in org.apache.commons.math3.ml.clustering.evaluation with parameters of type DistanceMeasure

Constructor	Description
ClusterEvaluator(DistanceMeasure measure)	Creates a new cluster evaluator with the given distance measure.
SumOfClusterVariances(DistanceMeasure measure)

Uses of DistanceMeasure in org.apache.commons.math3.ml.distance

Classes in org.apache.commons.math3.ml.distance that implement DistanceMeasure

Modifier and Type	Class	Description
class	CanberraDistance	Calculates the Canberra distance between two points.
class	ChebyshevDistance	Calculates the L∞ (max of abs) distance between two points.
class	EarthMoversDistance	Calculates the Earh Mover's distance (also known as Wasserstein metric) between two distributions.
class	EuclideanDistance	Calculates the L2 (Euclidean) distance between two points.
class	ManhattanDistance	Calculates the L1 (sum of abs) distance between two points.

Uses of DistanceMeasure in org.apache.commons.math3.ml.neuralnet

Methods in org.apache.commons.math3.ml.neuralnet with parameters of type DistanceMeasure

Modifier and Type	Method	Description
static int[][]	MapUtils.computeHitHistogram(java.lang.Iterable<double[]> data, NeuronSquareMesh2D map, DistanceMeasure distance)	Computes the "hit" histogram of a two-dimensional map.
static double	MapUtils.computeQuantizationError(java.lang.Iterable<double[]> data, java.lang.Iterable<Neuron> neurons, DistanceMeasure distance)	Computes the quantization error.
static double	MapUtils.computeTopographicError(java.lang.Iterable<double[]> data, Network net, DistanceMeasure distance)	Computes the topographic error.
static double[][]	MapUtils.computeU(NeuronSquareMesh2D map, DistanceMeasure distance)	Computes the U-matrix of a two-dimensional map.
static Neuron	MapUtils.findBest(double[] features, java.lang.Iterable<Neuron> neurons, DistanceMeasure distance)	Finds the neuron that best matches the given features.
static Pair<Neuron,Neuron>	MapUtils.findBestAndSecondBest(double[] features, java.lang.Iterable<Neuron> neurons, DistanceMeasure distance)	Finds the two neurons that best match the given features.
static Neuron[]	MapUtils.sort(double[] features, java.lang.Iterable<Neuron> neurons, DistanceMeasure distance)	Creates a list of neurons sorted in increased order of the distance to the given features.

Uses of DistanceMeasure in org.apache.commons.math3.ml.neuralnet.sofm

Fields in org.apache.commons.math3.ml.neuralnet.sofm declared as DistanceMeasure

Modifier and Type	Field	Description
private DistanceMeasure	KohonenUpdateAction.distance	Distance function.

Constructors in org.apache.commons.math3.ml.neuralnet.sofm with parameters of type DistanceMeasure

Constructor	Description
KohonenUpdateAction(DistanceMeasure distance, LearningFactorFunction learningFactor, NeighbourhoodSizeFunction neighbourhoodSize)

Uses of DistanceMeasure in org.apache.commons.math3.ml.neuralnet.twod.util

Fields in org.apache.commons.math3.ml.neuralnet.twod.util declared as DistanceMeasure

Modifier and Type	Field	Description
private DistanceMeasure	HitHistogram.distance	Distance.
private DistanceMeasure	QuantizationError.distance	Distance.
private DistanceMeasure	SmoothedDataHistogram.distance	Distance.
private DistanceMeasure	TopographicErrorHistogram.distance	Distance.
private DistanceMeasure	UnifiedDistanceMatrix.distance	Distance.

Constructors in org.apache.commons.math3.ml.neuralnet.twod.util with parameters of type DistanceMeasure

Constructor	Description
HitHistogram(boolean normalizeCount, DistanceMeasure distance)
QuantizationError(DistanceMeasure distance)
SmoothedDataHistogram(int smoothingBins, DistanceMeasure distance)
TopographicErrorHistogram(boolean relativeCount, DistanceMeasure distance)
UnifiedDistanceMatrix(boolean individualDistances, DistanceMeasure distance)	Simple constructor.