attributeweightsapplier.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.Operator;
import edu.udo.cs.yale.operator.IOObject;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.operator.UserError;
import edu.udo.cs.yale.operator.parameter.*;
import edu.udo.cs.yale.example.AttributeWeights;
import edu.udo.cs.yale.example.AttributeWeightedExampleSet;
import edu.udo.cs.yale.example.WeightApplier;
import edu.udo.cs.yale.example.Example;
import edu.udo.cs.yale.example.ExampleSet;
import edu.udo.cs.yale.tools.LogService;

import java.util.List;

/** This operator deselects attributes with a weight value of 0.0. The values of the other 
 *  numeric attributes will be recalculated based on the {@link WeightApplier} and the weights 
 *  delivered as {@link AttributeWeights} object in the input.
 *
 *  @version $Id: AttributeWeightsApplier.java,v 2.3 2004/08/27 11:57:36 ingomierswa Exp $
 */
public class AttributeWeightsApplier extends Operator {

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

    public IOObject[] apply() throws OperatorException {
	String weightFile      = getParameterAsString("attribute_weight_file"); 
  	AttributeWeights weights = (AttributeWeights)getInput(AttributeWeights.class);
	ExampleSet exampleSet  = (ExampleSet)getInput(ExampleSet.class);

	AttributeWeightedExampleSet weightedSet = new AttributeWeightedExampleSet(exampleSet, weights);
	String weightApplierName = getParameterAsString("weight_applier");
	WeightApplier weightApplier = null;
	try {
	    weightApplier = (WeightApplier)Class.forName(weightApplierName).newInstance();
	} catch (Exception e) { throw new UserError(this, e, 904, new Object[] { getName(), e}); }
	weightedSet.setWeightApplier(weightApplier);
	ExampleSet result = weightedSet.createExampleSetFromWeights();

	return new IOObject[] { result };
    }

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


    public List getParameterTypes() {
	List types = super.getParameterTypes();
	ParameterType type = new ParameterTypeStringCategory("weight_applier", 
							     "The fully qualified classname of the weight applier.", 
							     new String[] { "edu.udo.cs.yale.example.ScalingWeightApplier", 
									    "edu.udo.cs.yale.example.DummyWeightApplier"}, 
							     "edu.udo.cs.yale.example.ScalingWeightApplier");
	type.setExpert(false);
	types.add(type);
	return types;
    }
}