| Package | Description | 
|---|---|
| org.hipparchus.clustering | Clustering algorithms. | 
| org.hipparchus.clustering.evaluation | Cluster evaluation methods. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | CentroidCluster<T extends Clusterable>A Cluster used by centroid-based clustering algorithms. | 
| class  | Cluster<T extends Clusterable>Cluster holding a set of  Clusterablepoints. | 
| 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 Type | Class and Description | 
|---|---|
| class  | DoublePointA simple implementation of  Clusterablefor points with double coordinates. | 
| Modifier and Type | Method and Description | 
|---|---|
| Clusterable | CentroidCluster. getCenter()Get the point chosen to be the center of this cluster. | 
| Modifier and Type | Method and Description | 
|---|---|
| protected double | Clusterer. distance(Clusterable p1,
        Clusterable p2)Calculates the distance between two  Clusterableinstances
 with the configuredDistanceMeasure. | 
| Constructor and Description | 
|---|
| CentroidCluster(Clusterable center)Build a cluster centered at a specified point. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | 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 Type | Method and Description | 
|---|---|
| protected Clusterable | ClusterEvaluator. centroidOf(Cluster<T> cluster)Computes the centroid for a cluster. | 
| Modifier and Type | Method and Description | 
|---|---|
| protected double | ClusterEvaluator. distance(Clusterable p1,
        Clusterable p2)Calculates the distance between two  Clusterableinstances
 with the configuredDistanceMeasure. | 
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