Package org.encog.ml.data.folded

Examples of org.encog.ml.data.folded.FoldedDataSet


    network.reset();
    return network;
  }

  public void train(BasicNetwork network, MLDataSet training) {
    final FoldedDataSet folded = new FoldedDataSet(training);
    final MLTrain train = new ResilientPropagation(network, folded);
    final CrossValidationKFold trainFolded = new CrossValidationKFold(train,4);

    int epoch = 1;
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  private ProjectEGFile mlMethod;
  private EncogCommonTab parentTab;
 
  private MLDataSet wrapTrainingData(MLDataSet trainingData) {
    final FoldedDataSet folded = new FoldedDataSet(trainingData);
    return folded;
  }
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  {
    MLDataSet trainingData = XOR.createNoisyXORDataSet(10);
   
    BasicNetwork network = NetworkUtil.createXORNetworkUntrained();
   
    final FoldedDataSet folded = new FoldedDataSet(trainingData);
    final MLTrain train = new ResilientPropagation(network, folded);
    final CrossValidationKFold trainFolded = new CrossValidationKFold(train,4);
   
    EncogUtility.trainToError(trainFolded, 0.2);
   
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    final File trainingFile = getScript().resolveFilename(trainingID);

    MLDataSet trainingSet = EncogUtility.loadEGB2Memory(trainingFile);

    if (this.kfold > 0) {
      trainingSet = new FoldedDataSet(trainingSet);
    }

    return trainingSet;
  }
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    final File trainingFile = getScript().resolveFilename(trainingID);

    MLDataSet trainingSet = EncogUtility.loadEGB2Memory(trainingFile);

    if (this.kfold > 0) {
      trainingSet = new FoldedDataSet(trainingSet);
    }

    return trainingSet;
  }
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  {
    MLDataSet trainingData = XOR.createNoisyXORDataSet(10);
   
    BasicNetwork network = NetworkUtil.createXORNetworkUntrained();
   
    final FoldedDataSet folded = new FoldedDataSet(trainingData);
    final MLTrain train = new ResilientPropagation(network, folded);
    final CrossValidationKFold trainFolded = new CrossValidationKFold(train,4);
   
    EncogUtility.trainToError(trainFolded, 0.2);
   
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