statisticssettings.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.Statistics;

import java.util.Vector;

import com.prudsys.pdm.Core.MiningAttribute;
import com.prudsys.pdm.Core.MiningModel;
import com.prudsys.pdm.Core.MiningSettings;

/**
  * Parameters for computing statistic-based models. <p>
  *
  * From CWM Data Mining. <p>
  *
  * Superclasses:
  * <ul>
  *   <li> MiningSettings
  * </ul>
  * Constraints:
  * <ul>
  *   <li> Function must specify "StatisticalAnalysis".
  * </ul>
  *
  * Additions from PDM CWM extension. <p>
  *
  * References added:
  * <ul>
  *   <li> <i>univariateTarget</i>: Reference MiningAttribute as Univariate Target. <br>
  *       - class: MiningAttribute <br>
  *       - multiplicity: exactly one
  *   <li> <i>multivariateTarget1</i>: Reference MiningAttribute as first Multivariate Target. <br>
  *       - class: MiningAttribute <br>
  *       - multiplicity: exactly one
  *   <li> <i>multivariateTarget2</i>: Reference MiningAttribute as second Multivariate Target. <br>
  *       - class: MiningAttribute <br>
  *       - multiplicity: exactly one
  * </ul>
  *
  * @see MiningAttribute
  */
public class StatisticsSettings extends MiningSettings
{
    private MiningAttribute univariateTarget;
    private MiningAttribute multivariateTarget1;
    private MiningAttribute multivariateTarget2;
    private Vector grouping = new Vector();

    /**
     * @roseuid 3C5EAB760036
     */
    public StatisticsSettings() {
        this.setFunction( MiningModel.STATISTICAL_ANALYSIS_FUNCTION );
    }

    /**
     * Verify settings. Call super class method (of MiningSettings) for
     * verifying settings and checks whether at least one target attribute
     * is defined. If settings are incomplete an illegal argument exception
     * is thrown.
     *
     * @exception IllegalArgumentException exception that is thrown for incomplete settings
     */
    public void verifySettings() throws IllegalArgumentException
    {
        super.verifySettings();
        if( univariateTarget == null )
        {
            if( multivariateTarget1 == null || multivariateTarget2 == null )
            {
                throw new IllegalArgumentException( "Attribute Target can't be null." );
            }
        }
    }

    /**
     * Get vector of grouping attributes (elements are of the type
     * GroupingParameter).
     *
     * @return vector of grouping attributes
     * @see GroupingParameter
     */
    public Vector getGrouping()
    {
        return grouping;
    }

    /**
     * Sets vector of grouping attributes (elements must be of the type
     * GroupingParameter).
     *
     * @param grouping new vector of grouping attributes
     * @see GroupingParameter
     */
    public void setGrouping(Vector grouping)
    {
        this.grouping = grouping;
    }

    /**
     * Returns univariate target attribute.
     *
     * @return univariate target attribute
     */
    public MiningAttribute getUnivariateTarget() {

      return univariateTarget;
    }

    /**
     * Sets univariate target attribute.
     *
     * @param uniTarget new univariate target attribute
     */
    public void setUnivariateTarget(MiningAttribute uniTarget) {

      this.univariateTarget = uniTarget;
    }

    /**
     * Returns first multivariate target attribute.
     *
     * @return first multivariate target attribute
     */
    public MiningAttribute getMultivariateTarget1()
    {
        return multivariateTarget1;
    }

    /**
     * Sets first multivariate target attribute.
     *
     * @param multivariateTarget1 first multivariate target attribute
     */
    public void setMultivariateTarget1(MiningAttribute multivariateTarget1)
    {
        this.multivariateTarget1 = multivariateTarget1;
    }

    /**
     * Returns second multivariate target attribute.
     *
     * @return second multivariate target attribute
     */
    public MiningAttribute getMultivariateTarget2()
    {
        return multivariateTarget2;
    }

    /**
     * Sets second multivariate target attribute.
     *
     * @param multivariateTarget2 second multivariate target attribute
     */
    public void setMultivariateTarget2(MiningAttribute multivariateTarget2)
    {
        this.multivariateTarget2 = multivariateTarget2;
    }

    /**
     * Returns settings as string.
     *
     * @return settings as string
     */
    public String toString()
    {
        return "Statistics";
    }

    /**
     * Returns settings as HTML string.
     *
     * @return settings as HTML string
     */
    public String toHtmlString()
    {
        String description = "Model type:<br>Statistics<br>";
        return description;
    }

}