Package com.datumbox.framework.core.machinelearning.clustering

Class Summary

Class	Description
GaussianDPMM	The GaussianDPMM implements Dirichlet Process Mixture Models with Multivariate Normal and Normal-Inverse-Wishart prior.
GaussianDPMM.Cluster	The AbstractCluster class of the GaussianDPMM model.
GaussianDPMM.ModelParameters	Base class for every ModelParameter class in the framework.
GaussianDPMM.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
HierarchicalAgglomerative	This class implements the Hierarchical Agglomerative clustering algorithm supporting different Linkage and Distance methods.
HierarchicalAgglomerative.Cluster
HierarchicalAgglomerative.ModelParameters	Base class for every ModelParameter class in the framework.
HierarchicalAgglomerative.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
Kmeans	This class implements the K-means clustering algorithm supporting different Initialization and distance methods.
Kmeans.Cluster
Kmeans.ModelParameters	Base class for every ModelParameter class in the framework.
Kmeans.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
MultinomialDPMM	The MultinomialDPMM implements Dirichlet Process Mixture Models with Multinomial and Dirichlet priors.
MultinomialDPMM.Cluster	The AbstractCluster class of the MultinomialDPMM model.
MultinomialDPMM.ModelParameters	Base class for every ModelParameter class in the framework.
MultinomialDPMM.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.

Enum Summary

Enum	Description
HierarchicalAgglomerative.TrainingParameters.Distance	The Distance method used in the calculations.
HierarchicalAgglomerative.TrainingParameters.Linkage	The Linkage method used in the calculations.
Kmeans.TrainingParameters.Distance	The Distance method used in the calculations.
Kmeans.TrainingParameters.Initialization	The Initialization method that we use.