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#Org.apache.commons.math3.ml.clustering Classes and Interfaces - 12 results found.
NameDescriptionTypePackageFramework
CentroidClusterA Cluster used by centroid-based clustering algorithms.Classorg.apache.commons.math3.ml.clusteringApache Commons
ClusterCluster holding a set of Clusterable points.Classorg.apache.commons.math3.ml.clusteringApache Commons
ClusterableInterface for n-dimensional points that can be clustered together.Interfaceorg.apache.commons.math3.ml.clusteringApache Commons
ClustererBase class for clustering algorithms.Classorg.apache.commons.math3.ml.clusteringApache Commons
ClusterEvaluatorBase class for cluster evaluation methods.Classorg.apache.commons.math3.ml.clustering.evaluationApache Commons
DBSCANClustererDBSCAN (density-based spatial clustering of applications with noise) algorithm.Classorg.apache.commons.math3.ml.clusteringApache Commons
DoublePointA simple implementation of Clusterable for points with double coordinates.Classorg.apache.commons.math3.ml.clusteringApache Commons
FuzzyKMeansClustererFuzzy K-Means clustering algorithm.Classorg.apache.commons.math3.ml.clusteringApache Commons
KMeansPlusPlusClustererClustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.Classorg.apache.commons.math3.ml.clusteringApache Commons
KMeansPlusPlusClusterer .EmptyClusterStrategyStrategies to use for replacing an empty cluster.Classorg.apache.commons.math3.ml.clustering.KMeansPlusPlusClustererApache Commons
MultiKMeansPlusPlusClustererA wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.Classorg.apache.commons.math3.ml.clusteringApache Commons
SumOfClusterVariancesComputes the sum of intra-cluster distance variances according to the formula: \( score = \sum\limits_{i=1}^n \sigma_i^2 \)Classorg.apache.commons.math3.ml.clustering.evaluationApache Commons