protected CrossTraining(IMLMethod network, FoldedDataSet training)
: base(TrainingImplementationType.Iterative)
{
this._x87a7fc6a72741c2e = network;
this.Training = training;
this._x3952df2eab48841c = training;
}
/// <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;
}
/// <summary>
/// Open an additional dataset.
/// </summary>
/// <returns>The dataset.</returns>
public IMLDataSet OpenAdditional()
{
var folded = new FoldedDataSet(_underlying.OpenAdditional())
{
Owner = this
};
return(folded);
}
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>
/// Open an additional dataset.
/// </summary>
/// <returns>The dataset.</returns>
public IMLDataSet OpenAdditional()
{
var folded = new FoldedDataSet(_underlying.OpenAdditional()) {Owner = this};
return folded;
}
/// <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;
}
/// <summary>
/// Construct an enumerator.
/// </summary>
/// <param name="owner">The owner.</param>
public FoldedEnumerator(FoldedDataSet owner)
{
_owner = owner;
_currentIndex = -1;
}
private IMLDataSet x13d6d581f93d9ea3()
{
IMLDataSet set;
string propertyString = base.Prop.GetPropertyString("ML:CONFIG_trainingFile");
FileInfo filename = base.Script.ResolveFilename(propertyString);
if (1 != 0)
{
set = EncogUtility.LoadEGB2Memory(filename);
while (this._x33d31451731666c6 > 0)
{
do
{
set = new FoldedDataSet(set);
}
while (-1 == 0);
if (-2147483648 != 0)
{
return set;
}
}
return set;
}
return set;
}
