Uses of Interface
org.apache.commons.math3.ml.distance.DistanceMeasure
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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. -
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Uses of DistanceMeasure in org.apache.commons.math3.ml.clustering
Methods in org.apache.commons.math3.ml.clustering that return DistanceMeasure Modifier and Type Method Description DistanceMeasure
Clusterer. getDistanceMeasure()
Returns theDistanceMeasure
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 givenDistanceMeasure
.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
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)
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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(Iterable<double[]> data, NeuronSquareMesh2D map, DistanceMeasure distance)
Computes the "hit" histogram of a two-dimensional map.static double
MapUtils. computeQuantizationError(Iterable<double[]> data, Iterable<Neuron> neurons, DistanceMeasure distance)
Computes the quantization error.static double
MapUtils. computeTopographicError(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, Iterable<Neuron> neurons, DistanceMeasure distance)
Finds the neuron that best matches the given features.static Pair<Neuron,Neuron>
MapUtils. findBestAndSecondBest(double[] features, Iterable<Neuron> neurons, DistanceMeasure distance)
Finds the two neurons that best match the given features.static Neuron[]
MapUtils. sort(double[] features, Iterable<Neuron> neurons, DistanceMeasure distance)
Creates a list of neurons sorted in increased order of the distance to the givenfeatures
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Uses of DistanceMeasure in org.apache.commons.math3.ml.neuralnet.sofm
Constructors in org.apache.commons.math3.ml.neuralnet.sofm with parameters of type DistanceMeasure Constructor Description KohonenUpdateAction(DistanceMeasure distance, LearningFactorFunction learningFactor, NeighbourhoodSizeFunction neighbourhoodSize)
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Uses of DistanceMeasure in org.apache.commons.math3.ml.neuralnet.twod.util
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.
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