/*
* 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.neural.networks.training;
import org.encog.neural.data.NeuralDataSet;
import org.encog.neural.networks.BasicNetwork;
/**
* Calculate a score based on a training set. This class allows simulated
* annealing or genetic algorithms just as you would any other training set
* based training method.
*/
public class TrainingSetScore implements CalculateScore {
/**
* The training set.
*/
private final NeuralDataSet training;
/**
* Construct a training set score calculation.
*
* @param training
* The training data to use.
*/
public TrainingSetScore(final NeuralDataSet training) {
this.training = training;
}
/**
* Calculate the score for the network.
* @param network The network to calculate for.
* @return The score.
*/
public double calculateScore(final BasicNetwork network) {
return network.calculateError(this.training);
}
/**
* A training set based score should always seek to lower the error,
* as a result, this method always returns true.
* @return Returns true.
*/
public boolean shouldMinimize() {
return true;
}
}