regressionalgorithm.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.Regression;

import com.prudsys.pdm.Core.MiningException;
import com.prudsys.pdm.Core.MiningModel;
import com.prudsys.pdm.Core.MiningSettings;
import com.prudsys.pdm.Models.Supervised.SupervisedMiningAlgorithm;

/**
 * Base class for regression algorithms.
 */
public abstract class RegressionAlgorithm extends SupervisedMiningAlgorithm
{
  // -----------------------------------------------------------------------
  //  Constructor
  // -----------------------------------------------------------------------
  /**
   * Empty constructor.
   */
  public RegressionAlgorithm() {
  }

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

    return new RegressionSettings();
  }

  // -----------------------------------------------------------------------
  //  Run regression algorithm and build mining model
  // -----------------------------------------------------------------------
  /**
   * Builds regression model.
   *
   * @return regression model builded
   * @exception MiningException could not build model
   */
  public MiningModel buildModel() throws MiningException
  {
    runAlgorithm();
    RegressionMiningModel model = new RegressionMiningModel();
    model.setMiningSettings( miningSettings );
    model.setInputSpec( applicationInputSpecification );
    model.setClassifier(getClassifier());
    this.miningModel = model;
    return model;
  }

}