/* * Encog(tm) Core v2.5 - Java Version * http://www.heatonresearch.com/encog/ * http://code.google.com/p/encog-java/ * Copyright 2008-2010 Heaton Research, Inc. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * For more information on Heaton Research copyrights, licenses * and trademarks visit: * http://www.heatonresearch.com/copyright */ package org.encog.engine.network.train.prop; import org.encog.engine.data.EngineDataSet; import org.encog.engine.network.flat.FlatNetwork; /** * Train a flat network, using backpropagation. */ public class TrainFlatNetworkBackPropagation extends TrainFlatNetworkProp { /** * The learning rate. */ private double learningRate; /** * The momentum. */ private double momentum; /** * The last delta values. */ private double[] lastDelta; /** * Construct a backprop trainer for flat networks. * * @param network * The network to train. * @param training * The training data. * @param learningRate * The learning rate. * @param momentum * The momentum. */ public TrainFlatNetworkBackPropagation(final FlatNetwork network, final EngineDataSet training, final double learningRate, final double momentum) { super(network, training); this.momentum = momentum; this.learningRate = learningRate; this.lastDelta = new double[network.getWeights().length]; } /** * @return The last deltas. */ public double[] getLastDelta() { return this.lastDelta; } /** * @return the learningRate */ public double getLearningRate() { return this.learningRate; } /** * @return the momentum */ public double getMomentum() { return this.momentum; } /** * Set the last delta. * * @param ds * The last delta. */ public void setLastDelta(final double[] ds) { this.lastDelta = ds; } /** * Set the learning rate. * * @param rate * The learning rate. */ public void setLearningRate(final double rate) { this.learningRate = rate; } /** * Set the momentum. * * @param rate * The momentum. */ public void setMomentum(final double rate) { this.momentum = rate; } /** * Update a weight. * * @param gradients * The gradients. * @param lastGradient * The last gradients. * @param index * The index. * @return The weight delta. */ @Override public double updateWeight(final double[] gradients, final double[] lastGradient, final int index) { final double delta = (gradients[index] * this.learningRate) + (this.lastDelta[index] * this.momentum); this.lastDelta[index] = delta; return delta; } }