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

org.encog.ml.data.folded.FoldedDataSet
A folded data set allows you to "fold" the data into several equal(or nearly equal) datasets. You then have the ability to select which fold the dataset will process. This is very useful for crossvalidation. This dataset works off of an underlying dataset. By default there are no folds (fold size 1). Call the fold method to create more folds.

    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;

View Full Code Here


  private ProjectEGFile mlMethod;
  private EncogCommonTab parentTab;
  
  private MLDataSet wrapTrainingData(MLDataSet trainingData) {
    final FoldedDataSet folded = new FoldedDataSet(trainingData);
    return folded;
  }

View Full Code Here

  {
    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);

View Full Code Here

    final File trainingFile = getScript().resolveFilename(trainingID);


    MLDataSet trainingSet = EncogUtility.loadEGB2Memory(trainingFile);


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


    return trainingSet;
  }

View Full Code Here

    final File trainingFile = getScript().resolveFilename(trainingID);


    MLDataSet trainingSet = EncogUtility.loadEGB2Memory(trainingFile);


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


    return trainingSet;
  }

View Full Code Here

  {
    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);

View Full Code Here

TOP

Related Classes of org.encog.ml.data.folded.FoldedDataSet

org.encog.app.analyst.commands.Cmd

org.encog.app.analyst.commands.CmdTrain

org.encog.examples.neural.cross.CrossValidateSunspot

org.encog.ml.data.MLDataPair

org.encog.neural.networks.training.TestFolded

org.encog.neural.networks.training.TrainingError

org.encog.workbench.process.TrainBasicNetwork

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.