/*
* Encog(tm) Core v3.4 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2016 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.
*
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package org.encog.ensemble.training;
import org.encog.ensemble.EnsembleTrainFactory;
import org.encog.ml.MLMethod;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.train.MLTrain;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.training.lma.LevenbergMarquardtTraining;
public class LevenbergMarquardtFactory implements EnsembleTrainFactory {
@Override
public MLTrain getTraining(MLMethod mlMethod, MLDataSet trainingData) {
return this.getTraining(mlMethod, trainingData, 0);
}
@Override
public MLTrain getTraining(MLMethod mlMethod, MLDataSet trainingData, double dropoutRate) {
return (MLTrain) new LevenbergMarquardtTraining((BasicNetwork) mlMethod, trainingData);
}
@Override
public String getLabel() {
return "LMQ";
}
@Override
public void setDropoutRate(double rate) {
throw new RuntimeException("LMQ does not support dropout rates");
}
}