Package org.encog.ml

Examples of org.encog.ml.CalculateScore

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  @Test
  public void testMLMethodGenetic() throws Throwable
  {
    MLDataSet trainingData = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);   
    CalculateScore score = new TrainingSetScore(trainingData);
    MLMethodGeneticAlgorithm genetic = new MLMethodGeneticAlgorithm(new MethodFactory(){
      @Override
      public MLMethod factor() {
        BasicNetwork network = NetworkUtil.createXORNetworkUntrained();
        network.reset();
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  public void eval(String start, String expect) {
    EncogProgramContext context = new EncogProgramContext();
    StandardExtensions.createNumericOperators(context);
    PrgPopulation pop = new PrgPopulation(context,1);
    CalculateScore score = new ZeroEvalScoreFunction();

    TrainEA genetic = new TrainEA(pop, score);
    genetic.setValidationMode(true);
    genetic.setCODEC(new PrgCODEC());
    genetic.addOperation(0.95, new SubtreeCrossover());
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    NEATPopulation pop = new NEATPopulation(2,1,1000);
    pop.setInitialConnectionDensity(1.0);// not required, but speeds training
    pop.reset();

    CalculateScore score = new TrainingSetScore(buffer);
    // train the neural network
   
    final EvolutionaryAlgorithm train = NEATUtil.constructNEATTrainer(pop,score);
   
    do {
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    MLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT, XOR.XOR_IDEAL);
    NEATPopulation pop = new NEATPopulation(2,1,1000);
    pop.setInitialConnectionDensity(1.0);// not required, but speeds training
    pop.reset();

    CalculateScore score = new TrainingSetScore(trainingSet);
    // train the neural network
   
    final EvolutionaryAlgorithm train = NEATUtil.constructNEATTrainer(pop,score);
   
    do {
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  @Test
  public void testAnneal() throws Throwable
  {
    MLDataSet trainingData = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);   
    FreeformNetwork network = NetworkUtil.createXORFreeformNetworkUntrained();
    CalculateScore score = new TrainingSetScore(trainingData);
    NeuralSimulatedAnnealing anneal = new NeuralSimulatedAnnealing(network,score,10,2,100);
    NetworkUtil.testTraining(trainingData,anneal,0.01);
  }
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  @Test
  public void testGenetic() throws Throwable
  {
    MLDataSet trainingData = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);   
    CalculateScore score = new TrainingSetScore(trainingData);
    MLMethodGeneticAlgorithm genetic = new MLMethodGeneticAlgorithm(new MethodFactory(){
      @Override
      public MLMethod factor() {
        FreeformNetwork network = NetworkUtil.createXORFreeformNetworkUntrained();
        network.reset();
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  public void testSort1() {
   
    MLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);
    NEATPopulation pop = new NEATPopulation(2,1,100);
    pop.reset();
    CalculateScore score = new TrainingSetScore(trainingSet);
    final EvolutionaryAlgorithm train = NEATUtil.constructNEATTrainer(pop,score);
       
    NEATGenome genome1 = new NEATGenome();
    genome1.setAdjustedScore(3.0);
    NEATGenome genome2 = new NEATGenome();
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  public void testSort2() {
   
    MLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);
    NEATPopulation pop = new NEATPopulation(2,1,100);
    pop.reset();
    CalculateScore score = new TrainingSetScore(trainingSet);
    final EvolutionaryAlgorithm train = NEATUtil.constructNEATTrainer(pop,score);
       
    NEATGenome genome1 = new NEATGenome();
    genome1.setAdjustedScore(3.0);
    NEATGenome genome2 = new NEATGenome();
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    final ParamsHolder holder = new ParamsHolder(args);

    final int particles = holder.getInt(
        MLTrainFactory.PROPERTY_PARTICLES, false, 20);
   
    CalculateScore score = new TrainingSetScore(training);
    Randomizer randomizer = new NguyenWidrowRandomizer();
   
    final MLTrain train = new NeuralPSO((BasicNetwork)method,randomizer,score,particles);
   
    return train;
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Related Classes of org.encog.ml.CalculateScore

  • org.encog.ml.factory.train.AnnealFactory
  • org.encog.ml.factory.train.EPLGAFactory
  • org.encog.ml.factory.train.GeneticFactory
  • org.encog.ml.factory.train.NEATGAFactory
  • org.encog.ml.factory.train.PSOFactory
  • org.encog.ml.prg.train.rewrite.TestRewriteAlgebraic
  • org.encog.neural.freeform.TestFreeformTraining
  • org.encog.neural.networks.neat.training.species.TestSortGenomesForSpecies
  • org.encog.neural.networks.training.TestNEAT
  • org.encog.neural.networks.training.TestTraining
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