public void Train()
{
var trainInput = DataPreparator.GetTrainInput();
var trainOutput = DataPreparator.GetTrainOutput();
var validateInput = DataPreparator.GetValidateInput();
var validateOutput = DataPreparator.GetValidateOutput();
var lastIndex = 0;
for (var i = 0; i < 9999; i++)
{
Classifier.Train(trainInput, trainOutput);
var mse = Validation.ValidateWithMse(validateInput, validateOutput);
var logLoss = Validation.ValidateWithLogLoss(validateInput, validateOutput);
LogLossList.Add(logLoss);
MseList.Add(mse);
if (mse < 0.01 || logLoss < 0.01)
{
Classifier.Save();
break;
}
else if (i - lastIndex > 500)
{
break;
}
else if (mse <= MseList.Min())
{
Classifier.Save();
lastIndex = i;
}
}
}
