Package org.apache.spark.ml.clustering

Interface Summary

Interface	Description
BisectingKMeansParams	Common params for BisectingKMeans and BisectingKMeansModel
GaussianMixtureParams	Common params for GaussianMixture and GaussianMixtureModel
KMeansParams	Common params for KMeans and KMeansModel
LDAParams
PowerIterationClusteringParams	Common params for PowerIterationClustering

Class Summary

Class	Description
BisectingKMeans	A bisecting k-means algorithm based on the paper "A comparison of document clustering techniques" by Steinbach, Karypis, and Kumar, with modification to fit Spark.
BisectingKMeansModel	Model fitted by BisectingKMeans.
BisectingKMeansSummary	Summary of BisectingKMeans.
ClusterData	Helper class for storing model data
ClusteringSummary	Summary of clustering algorithms.
DistributedLDAModel	Distributed model fitted by LDA.
ExpectationAggregator	ExpectationAggregator computes the partial expectation results.
GaussianMixture	Gaussian Mixture clustering.
GaussianMixtureModel	Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points are drawn from each Gaussian i with probability weights(i).
GaussianMixtureSummary	Summary of GaussianMixture.
InternalKMeansModelWriter	A writer for KMeans that handles the "internal" (or default) format
KMeans	K-means clustering with support for k-means|| initialization proposed by Bahmani et al.
KMeansModel	Model fitted by KMeans.
KMeansSummary	Summary of KMeans.
LDA	Latent Dirichlet Allocation (LDA), a topic model designed for text documents.
LDAModel	Model fitted by LDA.
LocalLDAModel	Local (non-distributed) model fitted by LDA.
PMMLKMeansModelWriter	A writer for KMeans that handles the "pmml" format
PowerIterationClustering	Power Iteration Clustering (PIC), a scalable graph clustering algorithm developed by Lin and Cohen.