attributeweightselection.java

一个很好的LIBSVM的JAVA源码。对于要研究和改进SVM算法的学者。可以参考。来自数据挖掘工具YALE工具包。

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2001-2004
 *      Simon Fischer, Ralf Klinkenberg, Ingo Mierswa, 
 *          Katharina Morik, Oliver Ritthoff
 *      Artificial Intelligence Unit
 *      Computer Science Department
 *      University of Dortmund
 *      44221 Dortmund,  Germany
 *  email: [e-mail]
 *  web:   http://yale.cs.uni-dortmund.de/
 *
 *  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., 59 Temple Place, Suite 330, Boston, MA 02111-1307
 *  USA.
 */
package edu.udo.cs.yale.operator.features;

import edu.udo.cs.yale.operator.parameter.*;
import edu.udo.cs.yale.operator.Operator;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.operator.IOObject;
import edu.udo.cs.yale.example.ExampleSet;
import edu.udo.cs.yale.example.Attribute;
import edu.udo.cs.yale.example.AttributeWeights;
import edu.udo.cs.yale.tools.LogService;

import java.util.List;

/** This operator selects all attributes which have a weight fulfilling a given condition. For
 *  example, only attributes with a weight greater than <code>min_weight</code> should be selected.
 *
 *  @version $Id: AttributeWeightSelection.java,v 1.5 2004/09/02 08:18:19 ingomierswa Exp $
 */
public class AttributeWeightSelection extends Operator {

    private static final String[] WEIGHT_RELATIONS = { "greater", "greater equals", "equals", "less equals", "less" };

    private static final int GREATER        = 0;
    private static final int GREATER_EQUALS = 1;
    private static final int EQUALS         = 2;
    private static final int LESS_EQUALS    = 3;
    private static final int LESS           = 4;

    private static final Class[] INPUT_CLASSES  = { ExampleSet.class, AttributeWeights.class };
    private static final Class[] OUTPUT_CLASSES = { ExampleSet.class };

    public IOObject[] apply() throws OperatorException {
	ExampleSet eSet = (ExampleSet)getInput(ExampleSet.class, false);
	AttributeWeights weights = (AttributeWeights)getInput(AttributeWeights.class);
	boolean deselectUnknown = getParameterAsBoolean("deselect_unknown");
	double relationWeight = getParameterAsDouble("weight");
	int relation = getParameterAsInt("weight_relation");
	boolean useAbsoluteWeights = getParameterAsBoolean("use_absolute_weights");
	for (int i = eSet.getNumberOfAttributes()-1; i >= 0; i--) {
	    Attribute attribute = eSet.getAttribute(i);
	    double weight = weights.getWeight(attribute.getName());
	    if (useAbsoluteWeights) weight = Math.abs(weight);
	    if (Double.isNaN(weight) && (deselectUnknown)) {
		eSet.removeAttribute(attribute);
	    } else {
		switch (relation) {
		    case GREATER: if (weight <= relationWeight) eSet.removeAttribute(attribute); break;
		    case GREATER_EQUALS: if (weight < relationWeight) eSet.removeAttribute(attribute); break;
		    case EQUALS: if (weight != relationWeight) eSet.removeAttribute(attribute); break;
		    case LESS_EQUALS: if (weight > relationWeight) eSet.removeAttribute(attribute); break;
		    case LESS: if (weight >= relationWeight) eSet.removeAttribute(attribute); break;
		}
	    }
	}
	return new IOObject[0];
    }

    public Class[] getInputClasses() { return INPUT_CLASSES; }
    public Class[] getOutputClasses() { return OUTPUT_CLASSES; }

    public List getParameterTypes() {
	List types = super.getParameterTypes();
	ParameterType type = new ParameterTypeDouble("weight", "Use this weight for the selection relation.", 
						     Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY, 1.0d);
	type.setExpert(false);
	types.add(type);
	type = new ParameterTypeCategory("weight_relation", "Selects only weights which fulfill this relation.", 
					 WEIGHT_RELATIONS, 0);
	type.setExpert(false);
	types.add(type);
	types.add(new ParameterTypeBoolean("deselect_unknown", 
					   "Indicates if attributes which weight is unknown should be deselected.", 
					   true));
	types.add(new ParameterTypeBoolean("use_absolute_weights", 
					   "Indicates if the absolute values of the weights should be used for comparison.", 
					   true));
	return types;
    }
}