/*
* 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.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.ensemble.aggregator;
import java.util.ArrayList;
import org.encog.ensemble.EnsembleAggregator;
import org.encog.ensemble.data.EnsembleDataSet;
import org.encog.ml.data.MLData;
import org.encog.ml.data.basic.BasicMLData;
public class Averaging implements EnsembleAggregator {
@Override
public MLData evaluate(ArrayList<MLData> outputs) {
int outputSize = outputs.get(0).size();
BasicMLData acc = new BasicMLData(outputSize);
for (MLData out: outputs)
{
acc = (BasicMLData) acc.plus(out);
}
acc = (BasicMLData) acc.times(1.0 / outputs.size());
return acc;
}
@Override
public String getLabel() {
return "averaging";
}
@Override
public void train() {
//This is a no-op in this aggregator
}
@Override
public void setTrainingSet(EnsembleDataSet trainingSet) {
// This is a no-op in this aggregator.
}
@Override
public boolean needsTraining() {
return false;
}
}