| Name | Description | Type | Package | Framework |
| CentroidCluster | A Cluster used by centroid-based clustering algorithms. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| Cluster | Cluster holding a set of Clusterable points. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| Clusterable | Interface for n-dimensional points that can be clustered together. | Interface | org.apache.commons.math3.ml.clustering | Apache Commons |
| Clusterer | Base class for clustering algorithms. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| ClusterEvaluator | Base class for cluster evaluation methods. | Class | org.apache.commons.math3.ml.clustering.evaluation | Apache Commons |
| DBSCANClusterer | DBSCAN (density-based spatial clustering of applications with noise) algorithm. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| DoublePoint | A simple implementation of Clusterable for points with double coordinates. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| FuzzyKMeansClusterer | Fuzzy K-Means clustering algorithm. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| KMeansPlusPlusClusterer | Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| KMeansPlusPlusClusterer .EmptyClusterStrategy | Strategies to use for replacing an empty cluster. | Class | org.apache.commons.math3.ml.clustering.KMeansPlusPlusClusterer | Apache Commons |
| MultiKMeansPlusPlusClusterer | A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution. | Class | org.apache.commons.math3.ml.clustering | Apache Commons |
| SumOfClusterVariances | Computes the sum of intra-cluster distance variances according to the formula: \( score = \sum\limits_{i=1}^n \sigma_i^2 \) | Class | org.apache.commons.math3.ml.clustering.evaluation | Apache Commons |