rbfnetworkoperator.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.
 *
 */

/*
* $Author$
* $Date$
* $Revision$
*/
package eti.bi.alphaminer.patch.standard.operation.operator;
import java.util.Vector;
import com.prudsys.pdm.Core.MiningAlgorithm;
import com.prudsys.pdm.Core.MiningAlgorithmSpecification;
import com.prudsys.pdm.Core.MiningAttribute;
import com.prudsys.pdm.Core.MiningException;
import com.prudsys.pdm.Core.MiningModel;
import com.prudsys.pdm.Core.NumericAttribute;
import com.prudsys.pdm.Models.Supervised.SupervisedMiningSettings;
import com.prudsys.pdm.Utils.GeneralUtils;
import eti.bi.alphaminer.core.handler.ICaseHandler;
import eti.bi.alphaminer.operation.operator.INodeInfo;
import eti.bi.alphaminer.operation.operator.ModelOperator;
import eti.bi.alphaminer.operation.operator.Operator;
import eti.bi.alphaminer.vo.BIData;
import eti.bi.alphaminer.vo.BIModel;
import eti.bi.alphaminer.vo.BIObject;
import eti.bi.alphaminer.vo.IBIData;
import eti.bi.alphaminer.vo.IBIModel;
import eti.bi.alphaminer.vo.IOperatorNode;
import eti.bi.common.Locale.Resource;
import eti.bi.exception.AppException;
import eti.bi.exception.SysException;

/* @author XiaoguangXu HITSZ-ICE*/
public class RBFNetworkOperator extends ModelOperator {

	public static String CLUSTERINGSEED = "clusteringseed";
	public static String MAXITS = "maxits";
	public static String NUMCLUSTERS = "numclusters";
	public static String RIDGE = "ridge";

	public static String DEFAULT_CLUSTERINGSEED = "1";
	public static String DEFAULT_MAXITS = "-1";
	public static String DEFAULT_NUMCLUSTERS = "20";
	public static String DEFAULT_RIDGE = "1.0e-8";

	/* Parameter name for MiningSettingSpecification and MiningAlgorithm */
	public static final String ALGORITHM_NAME = "RBFNetwork (Weka)";
	private static String MAP_WEKA_CLASS_PARAMETERS = "wekaClassParameters";

	/**
	 * @param a_CaseID
	 * @param a_CaseWindow
	 * @param aOperatorInfo
	 */
	public RBFNetworkOperator(String a_CaseID, INodeInfo aNodeInfo, ICaseHandler aCaseHandler) {
		super(a_CaseID, aNodeInfo, aCaseHandler);
		setDefaultModelName("RBFNetwork model");
		
		//2006/07/29 Xiaojun Chen
		PredictionAssessmentOperator.registerParentsDefinitionID(aNodeInfo.getDefinitionID());
		ScoreOperator.registerParentsDefinitionID(aNodeInfo.getDefinitionID());
	}

	/**
	 * 
	 */
	private static final long serialVersionUID = 1L;

	/**
	 * Set node id and update operator text of the DecisionTreeOperator at the same time.
	 * 
	 * @param a_NodeID
	 *            ID of the node
	 */
	public void setNodeID(String a_NodeID) {
		setLabel(getDescription() + " [" + a_NodeID + "]");
		setDefaultModelName(Resource.srcStr("RBFNetwork")+"_" + a_NodeID);
		super.setNodeID(a_NodeID);
	}

	/**
	 * Set node id and update operator text of the DecisionTreeOperator at the same time.
	 * 
	 * @param a_NodeID
	 *            ID of the node
	 */
	public void setDescription(String a_Description) {
		m_Description = a_Description;
		setLabel(m_Description + " [" + m_NodeID + "]");
		setDefaultModelName(Resource.srcStr("RBFNetwork")+"_" + m_NodeID);
	}

	@Override
	public void execute(IOperatorNode a_OperatorNode, Vector a_Parents) throws SysException, AppException,
			MiningException {
		// TODO 自动生成方法存根
		/* Get parameter from user input */

		String RBFNetworkparameter = "";

		String numclusters = (String) a_OperatorNode.getParameterValue(NUMCLUSTERS);
		if (numclusters == null) {
			numclusters= DEFAULT_NUMCLUSTERS;
		}
		RBFNetworkparameter += " -B " + numclusters;
		
		String ridge = (String) a_OperatorNode.getParameterValue(RIDGE);
		if (ridge == null) {
			ridge= DEFAULT_RIDGE;
		}
		RBFNetworkparameter += " -R " + ridge;

		String maxits = (String) a_OperatorNode.getParameterValue(MAXITS);
		if (maxits == null) {
			maxits = DEFAULT_MAXITS;
		}
		
		RBFNetworkparameter += " -M " + maxits;
		
		
		String clusteringseed = (String) a_OperatorNode.getParameterValue(CLUSTERINGSEED);
		if (clusteringseed == null) {
			clusteringseed = DEFAULT_CLUSTERINGSEED;
		}
		RBFNetworkparameter += " -S " + clusteringseed;
		
	
		/* Get input bi object from parent node */
		Operator parentOp = (Operator)a_Parents.elementAt(0);
		setInputBIObject(parentOp.getOutputBIObject());
		IBIData aInputBIData = getInputBIObject().getBIData();
		aInputBIData.getMiningStoredData().reset();
		
		/* Prepare output data model */
		BIData aOutputBIData = new BIData(getCaseID(), getNodeID());
		aOutputBIData.setTargetAttribute(aInputBIData.getTargetAttribute());
		aOutputBIData.setTransformActionHistory(aInputBIData.getTransformActionHistory());
		aOutputBIData.setTargetAttribute(aInputBIData.getTargetAttribute());
		aOutputBIData.setMiningStoredData(aInputBIData.getMiningStoredData());
		BIModel aOutputBIModel = new BIModel(getCaseID(), getNodeID(), IBIModel.TYPE_CLASSIFIER);
		
		

		/* Check attributes */
		MiningAttribute targetAttribute = aInputBIData.getTargetAttribute();
		aOutputBIModel.setTargetAttribute(targetAttribute);
		if (targetAttribute==null)
		{
			throw new AppException("Categorical Target attribute is missing. Please add target attribute by using Data Set Attribute Node.");
		}else if (targetAttribute instanceof NumericAttribute)
		{
			m_SystemMessageHandler.appendMessage("Attribute \""+targetAttribute.getName() + "\" is not Categorical.");
			throw new AppException("Attribute \""+targetAttribute.getName() + "\" should be Categorical.");
		}
		
		/*Create MiningSettings object and assign metadata*/
		SupervisedMiningSettings miningSettings = new SupervisedMiningSettings();
		miningSettings.setDataSpecification(aInputBIData.getMetaData());
		
		 /* Assign settings */
	    miningSettings.setTarget(targetAttribute);
	    try {
	    	miningSettings.verifySettings();
	    } catch (Exception e)
		{
	    	m_SystemMessageHandler.appendMessage("Invalid parameters in building the Decision Tree model.");
	    	throw new AppException("Invalid parameters in building the Decision Tree model.");
	    }	    
		
	    /* Set MiningSettings */
		aOutputBIModel.setMiningSettings(miningSettings);
		/* Get default mining algorithm specification from 'algorithms.xml' */
	    MiningAlgorithmSpecification miningAlgorithmSpecification =
	    MiningAlgorithmSpecification.getMiningAlgorithmSpecification( ALGORITHM_NAME, getNodeInfo());
	    
	    if( miningAlgorithmSpecification == null )
		      throw new MiningException( "Can't find RBFNerwork classification method." );
	    
	    /* Get class name from algorithms specification */
	    String className = miningAlgorithmSpecification.getClassname();
	    if( className == null )
	      throw new MiningException( "className attribute expected." );
	    
	    /* Set MiningAlgorithmSpecification */
		miningAlgorithmSpecification.setMAPValue(MAP_WEKA_CLASS_PARAMETERS, RBFNetworkparameter);
		aOutputBIModel.setMiningAlgorithmSpecification(miningAlgorithmSpecification);
		displayMiningAlgSpecParameters(miningAlgorithmSpecification);
	    
		 /* Set and display mining parameters */
	    GeneralUtils.displayMiningAlgSpecParameters(miningAlgorithmSpecification);
	    
	    /* Create algorithm object with default values */
	    MiningAlgorithm algorithm = GeneralUtils.createMiningAlgorithmInstance(className, this.getClass().getClassLoader());
						
		algorithm.setMiningInputStream(aInputBIData.getMiningStoredData());
		algorithm.setMiningSettings(miningSettings);
		algorithm.setMiningAlgorithmSpecification(miningAlgorithmSpecification);
		try
		{
			algorithm.verify();
		} catch(IllegalArgumentException e)
		{
			throw new MiningException(e.getMessage());
		}
		
		MiningModel model = algorithm.buildModel();
		
		m_SystemMessageHandler.appendMessage(Resource.srcStr("calculationtime")+" [s]: " + algorithm.getTimeSpentToBuildModel()+Resource.srcStr("ms"));
		m_SystemMessageHandler.nextLine();
		
		aOutputBIModel.setMiningModel(model);
		aOutputBIModel.setModelName(m_DefaultModelName);
		
		m_OutputBIObject.setBIData(aOutputBIData);	
		m_OutputBIObject.setBIModel(aOutputBIModel);
		
		//a_OperatorNode.setParameterValue("Temporary model", aOutputBIModel.getTempBIModelPath());		
		
		//aOutputBIModel.writeTempBIModel();
		
	}
	
	@Override
	/**
	 * Test if the NavieBayes Operator contains any results.
	 * @return true if NavieBayes Operator has result; false otherwise.
	 */
	public boolean hasResult() throws SysException {
		
		if (m_OutputBIObject != null)
		{
			return (m_OutputBIObject.hasResult(BIObject.DATA) &&
					m_OutputBIObject.hasResult(BIObject.MODEL));
		}else
		{
			return false;
		}
		
	}

}