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Package org.knime.base.node.mine.cluster.fuzzycmeans

The fuzzycmeans package contains all classes for the Fuzzy c-means node.

See:
          Description

Class Summary
ClusterMembershipFactory This CellFactory produces appended cells: for each DataRow the memberships to the cluster prototypes and the winner cluster in the last column.
FCMAlgorithm The Fuzzy c-means algorithm.
FCMAlgorithmMemory The Fuzzy c-means algorithm.
FCMQualityMeasures Utility class to compute several cluster quality measures based on a Fuzzy c-means clustering.
FuzzyClusterNodeDialog Dialog for FuzzyClusterNodeModel- allows to adjust number of clusters and other properties.
FuzzyClusterNodeFactory Create classes for fuzzy c-means Clustering NodeModel, NodeView and NodeDialogPane.
FuzzyClusterNodeModel Generate a fuzzy c-means clustering using a fixed number of cluster centers.
FuzzyClusterNodeView The FuzzyClusterNodeView provides the user with information about the quality of the clustering.
 

Package org.knime.base.node.mine.cluster.fuzzycmeans Description

The fuzzycmeans package contains all classes for the Fuzzy c-means node. The node has a dialog and a view. The ClusterMembershipFactory class produces the appended columns in a DataTable with the memberships and the winner prototype.

The FCMAlgorithm class is the implementation of the Fuzzy c.means algorithm itself. You can perform a clustering and obtain the cluster centers just by using this class alone.

The FCMAlgorithmMemory class does the Fuzzy c.means clustering in the memory instead of iterating over the DataTable.

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