mlpparameters.java

利用Java实现的神经网络工具箱

/*
 * $RCSfile: MLPParameters.java,v $
 * $Revision: 1.2 $
 * $Date: 2005/02/24 21:20:29 $
 *
 * NeuralNetworkToolkit
 * Copyright (C) 2004 Universidade de Brasília
 *
 * This file is part of NeuralNetworkToolkit.
 *
 * NeuralNetworkToolkit 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.
 *
 * NeuralNetworkToolkit 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 NeuralNetworkToolkit; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA - 02111-1307 - USA.
 */

package neuralnetworktoolkit.architectures.mlp;

import java.util.Vector;

import neuralnetworktoolkit.architectures.ArchitectureParameters;

/**
 * 
 */
public class MLPParameters extends ArchitectureParameters {
	
	protected int[] neurons;
	protected String[] activationFunctions;
	protected String initializationName;
	
	/* 
	 * @see neuralnetworktoolkit.architectures.ArchitectureParameters#configureDefault()
	 */
	public void configureDefault() {
		activationFunctions = new String[3];
		neurons = new int[4];
		
		neurons[0] = inputSize;
		neurons[1] = (inputSize + 1) / 2;
		neurons[2] = (inputSize + 1) / 2;
		neurons[3] = 1;
		
		activationFunctions[0] = "Tanh";
		activationFunctions[1] = "Tanh";
		activationFunctions[2] = "Tanh";
		
		initializationName = "NguyenWidrow";
		
	} //configureDefault()
	
	/**
	 * 
	 * @param activationFunctionsVector
	 * @param neuronsVector
	 * @param outputFunction
	 * @param outputNeurons
	 */
	public void configureLayers(Vector activationFunctionsVector,
			Vector neuronsVector, String outputFunction, int outputNeurons) {
		
		int j;
		
		activationFunctions = new String[activationFunctionsVector.size() + 1];
		neurons = new int[neuronsVector.size() + 2];
		
		neurons[0] = inputSize;
		neurons[neurons.length - 1] = outputNeurons;
		j = 1;
		for(int i = 0; i < neuronsVector.size(); i++) {
			neurons[j] = ((Integer)neuronsVector.elementAt(i)).intValue();
			j++;
			
		}
		
		activationFunctions[activationFunctions.length - 1] = outputFunction;
		j = 0;
		for(int i = 0; i < activationFunctionsVector.size(); i++) {
			activationFunctions[j] = (String)activationFunctionsVector.elementAt(i);
			j++;
			
		}
		
	} //configureLayers()

	/**
	 * @return Returns the activationFunctions.
	 */
	public String[] getActivationFunctions() {
		return activationFunctions;
		
	} //getActivationFunctions()
	
	/**
	 * @param activationFunctions The activationFunctions to set.
	 */
	public void setActivationFunctions(String[] activationFunctions) {
		this.activationFunctions = activationFunctions;
		
	} //setActivationFunctions()
	
	/**
	 * @return Returns the initializationName.
	 */
	public String getInitializationName() {
		return initializationName;
		
	} //getInitializationName()
	
	/**
	 * @param initializationName The initializationName to set.
	 */
	public void setInitializationName(String initializationName) {
		this.initializationName = initializationName;
		
	} //setInitializationName()
	
	/**
	 * @return Returns the neurons.
	 */
	public int[] getNeurons() {
		return neurons;
		
	} //getNeurons()
	
	/**
	 * @param neurons The neurons to set.
	 */
	public void setNeurons(int[] neurons) {
		this.neurons = neurons;
		
	} //setNeurons()
	
} //MLPParameters