Package edu.cmu.tetrad.cluster

Interface ClusteringAlgorithm

All Known Implementing Classes:
KMeans
public interface ClusteringAlgorithm
Represents a clustering algorithm to cluster some data. The data is a TetradMatrix matrix with rows as cases and columns as variables. The purpose of this interface is to allow a clustering algorithm to have parameters set so that it can be passed to another class to do clustering on data.
Author:
Joseph Ramsey

  • Method Summary

    Modifier and Type
    Method
    Description
    void
    cluster(Matrix data)
    Clusters the given data set.
    List<List<Integer>>
    getClusters()
     
    void
    setVerbose(boolean verbose)
    True iff verbose output should be printed.

  • Method Details

    • cluster

      void cluster(Matrix data)
      Clusters the given data set.
      Parameters:
      data - An n x m double matrix with n cases (rows) and m variables (columns). Makes an int array c such that c[i] is the cluster that case i is placed into, or -1 if case i is not placed into a cluster (as a result of its being eliminated from consideration, for instance).

    • getClusters

      List<List<Integer>> getClusters()
      Returns:
      a list of clusters, each consisting of a list of indices in the dataset provided as an argument to cluster, or null if the data has not yet been clustered.

    • setVerbose

      void setVerbose(boolean verbose)
      True iff verbose output should be printed.