/// <summary>
/// Construct a cross trainer.
/// </summary>
/// <param name="network">The network.</param>
/// <param name="training">The training data.</param>
public CrossTraining(BasicNetwork network,
FoldedDataSet training)
{
this.network = network;
Training = training;
this.folded = training;
}
public void TestRPROPFolded()
{
IMLDataSet trainingData = XOR.CreateNoisyXORDataSet(10);
BasicNetwork network = NetworkUtil.CreateXORNetworkUntrained();
var folded = new FoldedDataSet(trainingData);
IMLTrain train = new ResilientPropagation(network, folded);
var trainFolded = new CrossValidationKFold(train, 4);
EncogUtility.TrainToError(trainFolded, 0.2);
XOR.VerifyXOR((IMLRegression)trainFolded.Method, 0.2);
}
/// <summary>
/// Obtain the training set.
/// </summary>
/// <returns>The training set.</returns>
private IMLDataSet ObtainTrainingSet()
{
String trainingID = Prop.GetPropertyString(
ScriptProperties.MlConfigTrainingFile);
FileInfo trainingFile = Script.ResolveFilename(trainingID);
IMLDataSet trainingSet = EncogUtility.LoadEGB2Memory(trainingFile);
if (_kfold > 0)
{
trainingSet = new FoldedDataSet(trainingSet);
}
return(trainingSet);
}
public NeuralNetworkModel(VersatileMLDataSet dataset)
{
dataset.NormHelper.NormStrategy = new BasicNormalizationStrategy(0, 1, 0, 1);
dataset.Normalize();
var inputs = dataset.NormHelper.InputColumns.Count;
var outputs = dataset.NormHelper.OutputColumns.Count;
var hiddens = (inputs + outputs) * 1.5;
var method = (BasicNetwork) new MLMethodFactory().Create(
MLMethodFactory.TypeFeedforward,
$"?:B->SIGMOID->{hiddens}:B->SIGMOID->?",
inputs,
outputs);
var folds = new FoldedDataSet(dataset);
folds.Fold(5);
var propTrainer = new ResilientPropagation(method, folds);
_kfoldTrainer = new CrossValidationKFold(propTrainer, 5);
}
/// <summary>
/// Construct a cross trainer.
/// </summary>
///
/// <param name="network">The network.</param>
/// <param name="training">The training data.</param>
protected CrossTraining(IMLMethod network, FoldedDataSet training) : base(TrainingImplementationType.Iterative)
{
_network = network;
Training = training;
_folded = training;
}
