distributionclusterer.java

一个数据挖掘系统的源码

/**
 *   
 *   AgentAcademy - an open source Data Mining framework for
 *   training intelligent agents
 *
 *   Copyright (C)   2001-2003 AA Consortium.
 *
 *   This library is open source software; you can redistribute it 
 *   and/or modify it under the terms of the GNU Lesser General 
 *   Public License as published by the Free Software Foundation;   
 *   either version 2.0 of the License, or (at your option) any later 
 *   version.
 *
 *   This library 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 Lesser General Public
 *   License along with this library; if not, write to the Free 
 *   Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, 
 *   MA  02111-1307 USA
 * 
 */

package org.agentacademy.modules.dataminer.clusterers;

/**
 * <p>Title: The Data Miner prototype</p>
 * <p>Description: A prototype for the DataMiner (DM), the Agent Academy (AA) module responsible for performing data mining on the contents of the Agent Use Repository (AUR). The extracted knowledge is to be sent back to the AUR in the form of a PMML document.</p>
 * <p>Copyright: Copyright (c) 2002</p>
 * <p>Company: CERTH</p>
 * @author asymeon
 * @version 0.3
 */

import org.agentacademy.modules.dataminer.core.*;

/**
 * Abstract clustering model that produces (for each test instance)
 * an estimate of the membership in each cluster
 * (ie. a probability distribution).
 *
 */
public abstract class DistributionClusterer extends Clusterer {

  // ===============
  // Public methods.
  // ===============

  /**
   * Computes the density for a given instance.
   *
   * @param instance the instance to compute the density for
   * @return the density.
   * @exception Exception if the density could not be computed
   * successfully
   */
  public abstract double densityForInstance(Instance instance)
    throws Exception;

  /**
   * Predicts the cluster memberships for a given instance.
   *
   * @param instance the instance to be assigned a cluster.
   * @return an array containing the estimated membership
   * probabilities of the test instance in each cluster (this
   * should sum to at most 1)
   * @exception Exception if distribution could not be
   * computed successfully
   */
  public abstract double[] distributionForInstance(Instance instance)
       throws Exception;

  /**
   * Assigns an instance to a Cluster.
   *
   * @param instance the instance to be classified
   * @return the predicted most likely cluster for the instance.
   * @exception Exception if an error occurred during the prediction
   */
  public int clusterInstance(Instance instance) throws Exception {
    double [] dist = distributionForInstance(instance);

    if (dist == null) {
      throw new Exception("Null distribution predicted");
    }

    if (Utils.sum(dist) <= 0) {
      throw new Exception("Unable to cluster instance");
    }
    return Utils.maxIndex(dist);
  }
}