Package org.encog.ml.train.strategy

Examples of org.encog.ml.train.strategy.Greedy

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    final MLTrain trainMain = new Backpropagation(network, trainingSet,0.000001, 0.0);

    ((Propagation)trainMain).setNumThreads(1);
    final StopTrainingStrategy stop = new StopTrainingStrategy();
    trainMain.addStrategy(new Greedy());
    trainMain.addStrategy(new HybridStrategy(trainAlt));
    trainMain.addStrategy(stop);

    int epoch = 0;
    while (!stop.shouldStop()) {
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    final MLTrain trainMain = new Backpropagation(network, trainingSet,0.000001, 0.0);

    ((Propagation)trainMain).setNumThreads(1);
    final StopTrainingStrategy stop = new StopTrainingStrategy();
    trainMain.addStrategy(new Greedy());
    trainMain.addStrategy(new HybridStrategy(trainAlt));
    trainMain.addStrategy(stop);

    int epoch = 0;
    while (!stop.shouldStop()) {
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    BasicNetwork network = (BasicNetwork)pattern.generate();
    MockTrain.setFirstElement(3.0,network);
   
    MockTrain mock = new MockTrain();
    mock.setNetwork(network);
    Greedy strategy = new Greedy();
    mock.addStrategy(strategy);
   
    // simulate an improvement
    mock.setError(0.01);
    mock.simulate(0.04, 5.0);
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    BasicNetwork network = (BasicNetwork)pattern.generate();
    MockTrain.setFirstElement(3.0,network);
   
    MockTrain mock = new MockTrain();
    mock.setNetwork(network);
    Greedy strategy = new Greedy();
    mock.addStrategy(strategy);
   
    // simulate an improvement
    mock.setError(0.01);
    mock.simulate(0.04, 5.0);
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Related Classes of org.encog.ml.train.strategy.Greedy

  • org.encog.examples.neural.recurrent.elman.ElmanXOR
  • org.encog.examples.neural.recurrent.jordan.JordanXOR
  • org.encog.neural.networks.training.TestStrategy
  • org.encog.neural.networks.training.TrainingError
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