/*
* 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.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0
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* distributed under the License is distributed on an "AS IS" BASIS,
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package org.encog.ensemble.bagging;
import java.util.ArrayList;
import junit.framework.TestCase;
import org.encog.engine.network.activation.ActivationSigmoid;
import org.encog.ensemble.EnsembleTrainFactory;
import org.encog.ensemble.aggregator.MajorityVoting;
import org.encog.ensemble.data.EnsembleDataSet;
import org.encog.ensemble.ml.mlp.factory.MultiLayerPerceptronFactory;
import org.encog.ensemble.training.ResilientPropagationFactory;
import org.encog.ml.data.MLData;
import org.encog.ml.data.MLDataSet;
import org.encog.neural.networks.XOR;
public class TestBagging extends TestCase {
int numSplits = 1;
int dataSetSize = 100;
MLDataSet trainingData;
public void testBagging() {
trainingData = XOR.createXORDataSet();
XOR.testXORDataSet(trainingData);
trainingData = new EnsembleDataSet(trainingData);
assertEquals(1,trainingData.getIdealSize());
assertEquals(2,trainingData.getInputSize());
EnsembleTrainFactory trainingStrategy = new ResilientPropagationFactory();
MultiLayerPerceptronFactory mlpFactory = new MultiLayerPerceptronFactory();
ArrayList<Integer> middleLayers = new ArrayList<Integer>();
middleLayers.add(4);
mlpFactory.setParameters(middleLayers, new ActivationSigmoid());
MajorityVoting mv = new MajorityVoting();
Bagging testBagging = new Bagging(numSplits, dataSetSize, mlpFactory, trainingStrategy, mv);
testBagging.setTrainingData(trainingData);
testBagging.train(1E-2,1E-2,(EnsembleDataSet) trainingData);
for (int j = 0; j < trainingData.size(); j++) {
MLData input = trainingData.get(j).getInput();
MLData result = testBagging.compute(input);
MLData should = trainingData.get(j).getIdeal();
for (int i = 0; i < trainingData.getIdealSize(); i++)
assertEquals(should.getData()[i],result.getData()[i]);
}
}
}