Package org.encog.ml.train

Examples of org.encog.ml.train.MLTrain


    if (this.trainingType == null) {
      throw new EncogError(
          "Please call selectTraining first to choose how to train.");
    }
    MLTrainFactory trainFactory = new MLTrainFactory();
    MLTrain train = trainFactory.create(method, dataset, this.trainingType,
        this.trainingArgs);
    return train;
  }
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      final MLDataSet training,
      final String type, final String args) {
   
    for (EncogPluginBase plugin : Encog.getInstance().getPlugins()) {
      if (plugin instanceof EncogPluginService1) {
        MLTrain result = ((EncogPluginService1) plugin).createTraining(
            method, training, type, args);
        if (result != null) {
          return result;
        }
      }
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        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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   * @return The lowest number of seconds that each of the ten attempts took.
   */
  public static int evaluateTrain(
      final BasicNetwork network, final MLDataSet training) {
    // train the neural network
    MLTrain train;
   
    train = new ResilientPropagation(network, training);

    final long start = System.currentTimeMillis();
    final long stop = start + (10 * MILIS);

    int iterations = 0;
    while (System.currentTimeMillis() < stop) {
      iterations++;
      train.iteration();
    }

    return iterations;
  }
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