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///////////////////////////////////////////////////////////////////////////////
// For information as to what this class does, see the Javadoc, below.       //
// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006,       //
// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard        //
// Scheines, Joseph Ramsey, and Clark Glymour.                               //
//                                                                           //
// This program is free software; you can redistribute it and/or modify      //
// it under the terms of the GNU General Public License as published by      //
// the Free Software Foundation; either version 2 of the License, or         //
// (at your option) any later version.                                       //
//                                                                           //
// This program is distributed in the hope that it will be useful,           //
// but WITHOUT ANY WARRANTY; without even the implied warranty of            //
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the             //
// GNU General Public License for more details.                              //
//                                                                           //
// You should have received a copy of the GNU General Public License         //
// along with this program; if not, write to the Free Software               //
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA //
///////////////////////////////////////////////////////////////////////////////

package edu.cmu.tetrad.cluster;

import edu.cmu.tetrad.util.Matrix;

import java.util.List;

/**
 * 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 josephramsey
 */
public interface ClusteringAlgorithm {

    /**
     * Clusters the given data set.
     *
     * @param 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).
     */
    void cluster(Matrix data);

    /**
     * @return 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.
     */
    List> getClusters();

    /**
     * True iff verbose output should be printed.
     */
    void setVerbose(boolean verbose);
}







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