decisiontreeserviceapibuild.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 Carsten Weisse
  * @author Michael Thess
  * @version 1.0
  */
package com.prudsys.pdm.Examples;

import java.io.FileWriter;

import com.prudsys.pdm.Adapters.ServiceAPI.LookupService;
import com.prudsys.pdm.Adapters.ServiceAPI.ServiceAlgorithmParameter;
import com.prudsys.pdm.Adapters.ServiceAPI.XelopesServiceImpl;
import com.prudsys.pdm.Core.MiningModel;
import com.prudsys.pdm.Utils.PmmlUtils;

/**
 * Builds same decision tree model like 'DecisionTreeBuild'
 * but using the Service API. Writes the model to the same
 * PMML file 'DecisionTreeModel.xml'.
 */
public class DecisionTreeServiceAPIBuild extends BasisExample
{
  /**
   * Empty constructor.
   */
  public DecisionTreeServiceAPIBuild()
  {
  }

  /**
   * Run the example of this class.
   *
   * @throws Exception error while example is running
   */
  public void runExample() throws Exception {

    // Create XELOPES Service Implementation object:
    XelopesServiceImpl xsi = new XelopesServiceImpl();

    // Want test string:
    String testString = xsi.getTestString();
    System.out.println("-->Test string: " + testString);

    // Want supported functions:
    String[] suppFunc = xsi.getSupportedFunctions();
    System.out.print("-->Supported functions: ");
    if (suppFunc != null)
      for (int i = 0; i < suppFunc.length; i++)
        System.out.print(suppFunc[i] + " ");
    System.out.println();

    // Want all supported algorithms:
    String[] suppAlg = xsi.getAllSupportedAlgorithms();
    System.out.print("-->Supported algorithms: ");
    if (suppAlg != null)
      for (int i = 0; i < suppAlg.length; i++)
        System.out.print(suppAlg[i] + " ");
    System.out.println();

    // Want all supported classification algorithms:
    String[] suppClassAlg = xsi.getSupportedAlgorithms(
                                MiningModel.CLASSIFICATION_FUNCTION );
    System.out.print("-->Supported classification algorithms: ");
    if (suppClassAlg != null)
      for (int i = 0; i < suppClassAlg.length; i++)
        System.out.print(suppClassAlg[i] + " ");
    System.out.println();

    // Want all algorithm parameters of algorithm 'Decision Tree (General)':
    String selectAlgo = suppClassAlg[0]; // general approach, classification
    selectAlgo = "Decision Tree (General)";  // want 'Decision Tree (General)'
    ServiceAlgorithmParameter[] algPar = xsi.getAlgorithmParameters(selectAlgo);
    System.out.println("-->Parameters of algorithm '" + selectAlgo + "':");
    if (algPar != null) {
      for (int i = 0; i < algPar.length; i++)
        System.out.println("     name: " + algPar[i].getName() +
                               " value: " + algPar[i].getValue() +
                               " type: " + algPar[i].getType() +
                               ", descript: " + algPar[i].getDescription() +
                               ", domain: " + algPar[i].getDomain() +
                               ", status: " + algPar[i].getStatus() +
                               ", ID: " + algPar[i].getID() +
                               ", childIDs: " + algPar[i].getChildIDs() );
    };

    // Want XELOPES data sources available for classification:
    String[] dataSource = xsi.getDataSources();
    System.out.print("-->Data sources for classification: ");
    if (dataSource != null)
      for (int i = 0; i < dataSource.length; i++)
        System.out.print(dataSource[i] + " ");
    System.out.println();

    // Run decision tree algorithm and obtain result as PMML string:
    System.out.println("-->Build model by service: ");
    String sourceName = "soybeanTrain";
    LookupService.setSAPValue(algPar, "minNodeSize", "0.3");
    LookupService.setSAPValue(algPar, "maxDepth", "100");
    LookupService.setSAPValue(algPar, "targetName", "class");
    String pmmlString = xsi.buildModelService(selectAlgo, algPar, sourceName);

    // Write result into PMML file:
    FileWriter writer = new FileWriter("data/pmml/DecisionTreeModel.xml");
    writer.write( pmmlString );
    writer.flush();

    // Show in browser:
    if (debug == 2) PmmlUtils.openPmmlBrowser("DecisionTreeModel.xml");

    // Apply model to test set:
    System.out.println("-->Apply model by service: ");
    sourceName = "soybeanTest";
    double[] values = xsi.applyModelFunctionService(pmmlString, sourceName);
    for (int i = 0; i < values.length; i++)
      System.out.println(i + ": " + values[i]);
  }

  /**
   * Simple example of building a decision tree
   * using the Service API.
   *
   * @param args arguments (ignored)
   */
  public static void main(String[] args) {

    try {
      new DecisionTreeServiceAPIBuild().runExample();
    }
    catch (Exception ex) {
      ex.printStackTrace();
    }
  }
}