/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 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.ml.mlp.factory;
import java.util.Collection;
import org.encog.engine.network.activation.ActivationFunction;
import org.encog.ensemble.EnsembleMLMethodFactory;
import org.encog.ml.MLMethod;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.layers.BasicLayer;
public class MultiLayerPerceptronFactory implements EnsembleMLMethodFactory {
Collection<Integer> layers;
ActivationFunction activation;
public void setParameters(Collection<Integer> layers, ActivationFunction activation){
this.layers=layers;
this.activation=activation;
}
@Override
public MLMethod createML(int inputs, int outputs) {
BasicNetwork network = new BasicNetwork();
network.addLayer(new BasicLayer(activation,false,inputs)); //(inputs));
for (Integer layerSize: layers)
network.addLayer(new BasicLayer(activation,true,layerSize));
network.addLayer(new BasicLayer(activation,true,outputs));
network.getStructure().finalizeStructure();
network.reset();
return network;
}
@Override
public String getLabel() {
String ret = "mlp{";
for (int i=0; i < layers.size() - 1; i++)
ret = ret + layers.toArray()[i] + ",";
return ret + layers.toArray()[layers.size() - 1] + "}";
}
@Override
public void reInit(MLMethod ml) {
((BasicNetwork) ml).reset();
}
}