private PerceptronTrainerStepPrediction TrainStepPredict()
{
State = PerceptronTrainerState.Training;
PerceptronTrainerStepPrediction result = new PerceptronTrainerStepPrediction();
PerceptronTrainerDatapoint CurrentDatapoint = Datapoints[CurrentTrainStep];
if (CurrentDatapoint.IsPositive)
{
result.DataPoint = CurrentDatapoint.Datapoint;
result.isPositiveDatapoint = true;
if (BiasedLearning)
{
return(PredictPositiveBiased(result));
}
else
{
return(PredictPositive(result));
}
}
else
{
result.DataPoint = CurrentDatapoint.Datapoint;
result.isPositiveDatapoint = false;
if (BiasedLearning)
{
return(PredictNegativeBiased(result));
}
else
{
return(PredictNegative(result));
}
}
}
public void TrainStep()
{
State = PerceptronTrainerState.Training;
PerceptronTrainerDatapoint CurrentDatapoint = Datapoints[CurrentTrainStep];
if (CurrentDatapoint.IsPositive)
{
if (BiasedLearning)
{
LearnPositiveBiased(CurrentDatapoint.Datapoint);
}
else
{
LearnPositive(CurrentDatapoint.Datapoint);
}
}
else
{
if (BiasedLearning)
{
LearnNegativeBiased(CurrentDatapoint.Datapoint);
}
else
{
LearnNegative(CurrentDatapoint.Datapoint);
}
}
if (CurrentTrainStep >= Datapoints.Count - 1)
{
CurrentTrainStep = 0;
LastPassErrors = Errors;
Runs++;
if (Errors == 0)
{
State = PerceptronTrainerState.Finished;
Convergence = true;
}
else
{
Errors = 0;
}
}
else
{
CurrentTrainStep++;
}
}
