Uses of Interface
org.hipparchus.clustering.Clusterable
Package
Description
Clustering algorithms.
Cluster evaluation methods.
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Uses of Clusterable in org.hipparchus.clustering
Modifier and TypeClassDescriptionclass
CentroidCluster<T extends Clusterable>
A Cluster used by centroid-based clustering algorithms.class
Cluster<T extends Clusterable>
Cluster holding a set ofClusterable
points.class
Clusterer<T extends Clusterable>
Base class for clustering algorithms.class
DBSCANClusterer<T extends Clusterable>
DBSCAN (density-based spatial clustering of applications with noise) algorithm.class
FuzzyKMeansClusterer<T extends Clusterable>
Fuzzy K-Means clustering algorithm.class
KMeansPlusPlusClusterer<T extends Clusterable>
Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.class
MultiKMeansPlusPlusClusterer<T extends Clusterable>
A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.Modifier and TypeClassDescriptionclass
A simple implementation ofClusterable
for points with double coordinates.Modifier and TypeMethodDescriptionCentroidCluster.getCenter()
Get the point chosen to be the center of this cluster.Modifier and TypeMethodDescriptionprotected double
Clusterer.distance
(Clusterable p1, Clusterable p2) Calculates the distance between twoClusterable
instances with the configuredDistanceMeasure
.ModifierConstructorDescriptionCentroidCluster
(Clusterable center) Build a cluster centered at a specified point. -
Uses of Clusterable in org.hipparchus.clustering.evaluation
Modifier and TypeClassDescriptionclass
ClusterEvaluator<T extends Clusterable>
Base class for cluster evaluation methods.class
SumOfClusterVariances<T extends Clusterable>
Computes the sum of intra-cluster distance variances according to the formula: \] score = \sum\limits_{i=1}^n \sigma_i^2 \] where n is the number of clusters and \( \sigma_i^2 \) is the variance of intra-cluster distances of cluster \( c_i \).Modifier and TypeMethodDescriptionprotected Clusterable
ClusterEvaluator.centroidOf
(Cluster<T> cluster) Computes the centroid for a cluster.Modifier and TypeMethodDescriptionprotected double
ClusterEvaluator.distance
(Clusterable p1, Clusterable p2) Calculates the distance between twoClusterable
instances with the configuredDistanceMeasure
.