multimodel.java

著名的开源仿真软件yale

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2002, 2003
 *      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.learner;

import edu.udo.cs.yale.operator.OperatorChain;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.operator.IOObject;
import edu.udo.cs.yale.operator.IllegalInputException;
import edu.udo.cs.yale.operator.IOContainer;
import edu.udo.cs.yale.example.Attribute;
import edu.udo.cs.yale.example.Example;
import edu.udo.cs.yale.example.ExampleSet;
import edu.udo.cs.yale.example.ExampleReader;
import edu.udo.cs.yale.example.MemoryExampleTable;
import edu.udo.cs.yale.tools.LogService;
import edu.udo.cs.yale.tools.TempFileService;

import java.io.*;

/** MultiModels are used for multi class learning tasks. A MultiModel contains a set of Models that can 
 *  handle only two-class decisions. */
public class MultiModel extends IOModel {

    public static final String ID = "YALE MultiModel";

    private static final int FILE_MODEL = 1;
    private static final int IO_MODEL = 2;

    private Model[] models;

    public MultiModel(Model[] models) {
	this.models = models;
    }

    public int getNumberOfModels() {
	return models.length;
    }

    /** Returns a binary decision model for the given classification index. */
    public Model getModel(int index) {
	return models[index];
    }

    /** Iterates over all classes of the label and applies one model for each class. For each example
     *  the predicted label is determined by choosing the model with the highest confidence. */
    public void apply(ExampleSet exampleSet) throws OperatorException {

	ExampleSet[] eSet   = new ExampleSet[getNumberOfModels()];
	
	for (int i = 0; i < getNumberOfModels(); i++) {
	    Model model = getModel(i);
	    model.setPredictionType(PREDICT_CONFIDENCE);
	    eSet[i] = (ExampleSet)exampleSet.clone();
	    eSet[i].createPredictedLabel();
	    model.apply(eSet[i]);
	}

	ExampleReader[] reader = new ExampleReader[eSet.length];
	for (int r = 0; r < reader.length; r++) 
	    reader[r] = eSet[r].getExampleReader();


	ExampleReader originalReader = exampleSet.getExampleReader();
	while (originalReader.hasNext()) {
	    double bestLabel = Double.NaN;
	    double highestFunctionValue = Double.NEGATIVE_INFINITY;
	    for (int k = 0; k < reader.length; k++) { 
		double functionValue = reader[k].next().getPredictedLabel();
		if (functionValue > highestFunctionValue) {
		    highestFunctionValue = functionValue;
		    bestLabel = k + Attribute.FIRST_CLASS_INDEX;
		}
	    }
	    originalReader.next().setPredictedLabel(bestLabel);
	}
    }

    /** Writes the models subsequently to the output stream. */
    public void writeData(ObjectOutputStream out) throws IOException {
	out.writeInt(models.length);
	for (int i = 0; i < models.length; i++) {
	    models[i].writeModel(out);
//  	    if (models[i] instanceof FileModel) {

//  		out.writeByte(FILE_MODEL);
//  		File modelfile = ((FileModel)models[i]).getModelFile();
//  		int filesize = (int)modelfile.length();
//  		out.writeInt(filesize);
//  		byte buffer[] = new byte[filesize];
//  		DataInputStream in = new DataInputStream(new FileInputStream(modelfile));
//  		in.readFully(buffer);
//  		in.close();
//  		out.write(buffer);

//  	    } else if (models[i] instanceof SerializableModel) {

//  		out.writeByte(IO_MODEL);
//  		out.writeObject(models[i]);

//  	    } else {
//  		LogService.logMessage("MultiModel.writeModel(File) cannot handle model of class '"+models[i].getClass()+"'", LogService.ERROR);
//  	    }
	}
    }

    /** Reads all models from the file. */
    public void readData(ObjectInputStream in) throws IOException, OperatorException {

	this.models = new Model[in.readInt()];
	for (int i = 0; i < models.length; i++) {
	    models[i] = Model.readModel(in);
//  	    int type = in.readByte();
//  	    switch(type) {
//  	    case IO_MODEL:
//  		models[i] = IOModel.readModel(in);
//  		break;

//  	    case FILE_MODEL:
//  		int filesize = in.readInt();
//  		byte buffer[] = new byte[filesize];
//  		in.readFully(buffer);
//  		File modelFile = TempFileService.createTempFile("multimodel_"+i+".mod");
//  		DataOutputStream out = new DataOutputStream(new FileOutputStream(modelFile));
//  		out.write(buffer);
//  		out.close();
//  		models[i] = new FileModel(modelFile);
//  		break;

//  	    default:
//  		LogService.logMessage("MultiModel.readModel(): unknown model type: "+type, LogService.ERROR);
//  		break;
//  	    }
	}
    }

    public String getIdentifier() { return ID; }

    public String toString() {
	String result = super.toString() + "\n";
	for (int i = 0; i < models.length; i++) 
	    result += (i>0?"\n":"") + models[i].toString();
	return result;
    }
}