clusteringalgorithm.java

一个数据挖掘软件ALPHAMINERR的整个过程的JAVA版源代码

/*
 *    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., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/**
 * Title: XELOPES Data Mining Library
 * Description: The XELOPES library is an open platform-independent and data-source-independent library for Embedded Data Mining.
 * Copyright: Copyright (c) 2002 Prudential Systems Software GmbH
 * Company: ZSoft (www.zsoft.ru), Prudsys (www.prudsys.com)
 * @author Valentine Stepanenko ([e-mail])
 * @version 1.0
 */

package com.prudsys.pdm.Models.Clustering;

import com.prudsys.pdm.Core.MiningAlgorithm;
import com.prudsys.pdm.Core.MiningException;
import com.prudsys.pdm.Core.MiningModel;
import com.prudsys.pdm.Core.MiningSettings;

/**
 * Base class for clustering algorithms.
 */
public abstract class ClusteringAlgorithm extends MiningAlgorithm
{
    // -----------------------------------------------------------------------
    //  Variables declarations
    // -----------------------------------------------------------------------
    /** Attribute name for output of cluster id values. */
    protected String clusterIdAttributeName;

    /** Upper limit for the number of computed clusters. */
    protected int maxNumberOfClusters;

    /** Distance between vectors to be clustered. */
    protected Distance distance;

    /** Array of clusters. */
    protected Cluster[] clusters;

    // -----------------------------------------------------------------------
    //  Constructor
    // -----------------------------------------------------------------------
    /**
     * Empty constructor.
     */
    public ClusteringAlgorithm()
    {
    }

    // -----------------------------------------------------------------------
    //  Getter and setter methods
    // -----------------------------------------------------------------------
    /**
     * Creates an instance of the clustering settings class that is required
     * to run the algorithm. The mining settings are assigned through the
     * setMiningSettings method.
     *
     * @return new instance of the clustering settings class of the algorithm
     */
    public MiningSettings createMiningSettings() {

      return new ClusteringSettings();
    }

    /**
     * Set clustering mining settings.
     *
     * @param miningSettings new clustering mining settings
     * @exception IllegalArgumentException mining settings are not of clustering type
     */
    public void setMiningSettings( MiningSettings miningSettings ) throws IllegalArgumentException
    {
        if( miningSettings instanceof ClusteringSettings )
        {
            super.setMiningSettings( miningSettings );
            ClusteringSettings clusteringSettings = (ClusteringSettings)miningSettings;
            this.clusterIdAttributeName = clusteringSettings.getClusterIdAttributeName();
            this.maxNumberOfClusters = clusteringSettings.getMaxNumberOfClusters();
            this.distance = clusteringSettings.getDistance();
        }
        else
        {
            throw new IllegalArgumentException( "MiningSettings have to be a ClusteringSettings." );
        }
    }

    /**
     * Returns all clusters.
     *
     * @return array of all clusters
     */
    protected Cluster[] getClusters()
    {
      return clusters;
    }

    /**
     * Sets all clusters.
     *
     * @param clusters new array of clusters
     */
    protected void setClusters(Cluster[] clusters)
    {
      this.clusters = clusters;
    }

    // -----------------------------------------------------------------------
    //  Run clustering algorithm and build mining model
    // -----------------------------------------------------------------------
    /**
     * Runs clustering algorithm.
     *
     * @exception MiningException cannot run algorithm
     */
    protected abstract void runAlgorithm() throws MiningException;

    /**
     * Build the mining model.
     *
     * @return clustering mining model created
     * @exception MiningException cannot build cluster model
     */
    public MiningModel buildModel() throws MiningException
    {
        runAlgorithm();
        ClusteringMiningModel model = new ClusteringMiningModel();
        model.setMiningSettings( miningSettings );
        model.setInputSpec( applicationInputSpecification );
        model.setClusters( getClusters() );
        model.setDistance( distance );
        this.miningModel = model;
        return model;
    }
}