Examples of addStrategy()

Examples of org.encog.ml.train.MLTrain.addStrategy()

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    // third, create the trainer
    MLTrainFactory trainFactory = new MLTrainFactory(); 
    MLTrain train = trainFactory.create(method,dataSet,trainerName,trainerArgs);       
    // reset if improve is less than 1% over 5 cycles
    if( method instanceof MLResettable && !(train instanceof ManhattanPropagation) ) {
      train.addStrategy(new RequiredImprovementStrategy(500));
    }

    // fourth, train and evaluate.
    EncogUtility.trainToError(train, 0.01);
    EncogUtility.evaluate((MLRegression)method, dataSet);
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Examples of org.encog.ml.train.MLTrain.addStrategy()

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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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Examples of org.encog.ml.train.MLTrain.addStrategy()

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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()) {
      trainMain.iteration();
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Examples of org.encog.ml.train.MLTrain.addStrategy()

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    ((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()) {
      trainMain.iteration();
      System.out.println("Training " + what + ", Epoch #" + epoch
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Examples of org.encog.ml.train.MLTrain.addStrategy()

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    // train the neural network
    final MLTrain train = new ResilientPropagation(network, trainingSet);
    // reset if improve is less than 1% over 5 cycles
    train.addStrategy(new RequiredImprovementStrategy(5));

    EncogUtility.trainToError(train, 0.01);
   
    EncogUtility.evaluate(network, trainingSet);
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Examples of org.encog.neural.networks.training.propagation.Propagation.addStrategy()

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      final Propagation train = new ResilientPropagation(network,
          useTraining);
      final StopTrainingStrategy strat = new StopTrainingStrategy(0.001,
          5);

      train.addStrategy(strat);
      train.setNumThreads(1); // force single thread mode

      for (int i = 0; (i < this.iterations) && !getShouldStop()
          && !strat.shouldStop(); i++) {
        train.iteration();
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Examples of org.encog.neural.networks.training.propagation.Propagation.addStrategy()

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    } else {
      train.setNumThreads(0);
    }

    for (final Strategy strategy : getStrategies()) {
      train.addStrategy(strategy);
    }

    setTrain(train);
  }
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Examples of org.encog.neural.networks.training.propagation.Propagation.addStrategy()

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    } else {
      train.setNumThreads(0);
    }

    for (final Strategy strategy : getStrategies()) {
      train.addStrategy(strategy);
    }

    setTrain(train);
  }
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Examples of org.encog.neural.networks.training.propagation.back.Backpropagation.addStrategy()

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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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Examples of org.encog.neural.networks.training.propagation.back.Backpropagation.addStrategy()

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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()) {
      trainMain.iteration();
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