weka.attributeSelection.AttributeSetEvaluator Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of weka-dev Show documentation

The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This version represents the developer version, the "bleeding edge" of development, you could say. New functionality gets added to this version.

There is a newer version: 3.9.6

Show newest version

/*
 *   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 3 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, see .
 */

 /*
 *    RELEASE INFORMATION (December 27, 2004)
 *    
 *    FCBF algorithm:
 *      Template obtained from Weka
 *      Developped for Weka by Zheng Alan Zhao   
 *      December 27, 2004
 *
 *    FCBF algorithm is a feature selection method based on Symmetrical Uncertainty 
 *    Measurement for relevance redundancy analysis. The details of FCBF algorithm are 
 *    in L. Yu and H. Liu. Feature selection for high-dimensional data: a fast 
 *    correlation-based filter solution. In Proceedings of the twentieth International 
 *    Conference on Machine Learning, pages 856--863, 2003.
 *    
 *    
 *    CONTACT INFORMATION
 *    
 *    For algorithm implementation:
 *    Zheng Zhao: zhaozheng at asu.edu
 *      
 *    For the algorithm:
 *    Lei Yu: leiyu at asu.edu
 *    Huan Liu: hliu at asu.edu
 *     
 *    Data Mining and Machine Learning Lab
 *    Computer Science and Engineering Department
 *    Fulton School of Engineering
 *    Arizona State University
 *    Tempe, AZ 85287
 *
 *    AttributeSetEvaluator.java
 *
 *    Copyright (C) 2004 Data Mining and Machine Learning Lab, 
 *                       Computer Science and Engineering Department, 
 *       		 Fulton School of Engineering, 
 *                       Arizona State University
 *
 */

package weka.attributeSelection;


/**
 * Abstract attribute set evaluator.
 *
 * @author Zheng Zhao: zhaozheng at asu.edu
 * @version $Revision: 8034 $
 */
public abstract class AttributeSetEvaluator extends ASEvaluation {
  
    /** for serialization */
    private static final long serialVersionUID = -5744881009422257389L;
  
    // ===============
    // Public methods.
    // ===============

    /**
     * evaluates an individual attribute
     *
     * @param attribute the index of the attribute to be evaluated
     * @return the "merit" of the attribute
     * @exception Exception if the attribute could not be evaluated
     */
    public abstract double evaluateAttribute(int attribute) throws Exception;

  /**
   * Evaluates a set of attributes
   *
   * @param attributes an int[] value
   * @param classAttributes an int[] value
   * @return a double value
   * @exception Exception if an error occurs
   */
  public abstract double evaluateAttribute(int[] attributes, int[] classAttributes) 
    throws Exception;
}