Examples of NEATTraining

Examples of org.encog.neural.neat.training.NEATTraining

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    CalculateScore score = new TrainingSetScore(trainingSet);
    // train the neural network
    ActivationStep step = new ActivationStep();
    step.setCenter(0.5);
   
    NEATTraining train = new NEATTraining(
        score, 2, 1, 10);
    //train.setOutputActivationFunction(step);
   
    return (NEATPopulation)train.getPopulation();
  }
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Examples of org.encog.neural.neat.training.NEATTraining

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    Assert.assertEquals(0.3,pop.getYoungScoreBonus());
   
    // see if the population can actually be used to train
    MLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT, XOR.XOR_IDEAL);   
    CalculateScore score = new TrainingSetScore(trainingSet);
    NEATTraining train = new NEATTraining(score,pop);
    train.iteration();

  }
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Examples of org.encog.neural.neat.training.NEATTraining

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    // train the neural network
    ActivationStep step = new ActivationStep();
    step.setCenter(0.5);
    pop.setOutputActivationFunction(step);
   
    final NEATTraining train = new NEATTraining(score,pop);
   
    EncogUtility.trainToError(train, 0.01);

    NEATNetwork network = (NEATNetwork)train.getMethod();

    network.clearContext();
    // test the neural network
    System.out.println("Neural Network Results:");
    EncogUtility.evaluate(network, trainingSet);
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Examples of org.encog.neural.neat.training.NEATTraining

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      if (dialog.getLoadToMemory().getValue()) {
        training = ((BufferedNeuralDataSet) training).loadToMemory();
      }

      CalculateScore score = new TrainingSetScore(training);
      NEATTraining train = new NEATTraining(score, pop);

      BasicTrainingProgress tab = new BasicTrainingProgress(train,
          popFile, train.getTraining());
      tab.setMaxError(dialog.getMaxError().getValue() / 100);
      EncogWorkBench.getInstance().getMainWindow().getTabManager().openTab(tab);

    }
  }
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