Package org.apache.spark.ml.clustering

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	:: Experimental :: Summary of BisectingKMeans.
ClusterData	Helper class for storing model data
ClusteringSummary	:: Experimental :: 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	:: Experimental :: 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	:: Experimental :: 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	:: Experimental :: Power Iteration Clustering (PIC), a scalable graph clustering algorithm developed by Lin and Cohen.