/// <summary>
/// Perform the training.
/// </summary>
/// <param name="train">The training method.</param>
/// <param name="method">The ML method.</param>
/// <param name="trainingSet">The training set.</param>
private void PerformTraining(IMLTrain train, IMLMethod method,
IMLDataSet trainingSet)
{
ValidateNetwork.ValidateMethodToData(method, trainingSet);
double targetError = Prop.GetPropertyDouble(
ScriptProperties.MlTrainTargetError);
Analyst.ReportTrainingBegin();
int maxIteration = Analyst.MaxIteration;
if (train.ImplementationType == TrainingImplementationType.OnePass)
{
train.Iteration();
Analyst.ReportTraining(train);
}
else
{
do
{
train.Iteration();
Analyst.ReportTraining(train);
} while ((train.Error > targetError) &&
!Analyst.ShouldStopCommand() &&
!train.TrainingDone &&
((maxIteration == -1) || (train.IterationNumber < maxIteration)));
}
train.FinishTraining();
Analyst.ReportTrainingEnd();
}
/// <summary>
/// </summary>
public override sealed bool ExecuteCommand(String args)
{
_kfold = ObtainCross();
IMLDataSet trainingSet = ObtainTrainingSet();
IMLMethod method = ObtainMethod();
IMLTrain trainer = CreateTrainer(method, trainingSet);
EncogLogging.Log(EncogLogging.LevelDebug, "Beginning training");
PerformTraining(trainer, method, trainingSet);
String resourceID = Prop.GetPropertyString(
ScriptProperties.MlConfigMachineLearningFile);
FileInfo resourceFile = Analyst.Script.ResolveFilename(
resourceID);
method = trainer.Method;
EncogDirectoryPersistence.SaveObject(resourceFile, method);
EncogLogging.Log(EncogLogging.LevelDebug, "save to:" + resourceID);
return(Analyst.ShouldStopCommand());
}