public void feedForward(double[] pattern)
{
lock (locker)
{
nn.feedForward(pattern);
}
}
public void TrainUntilAccuracy(double desired_accuracy, double desired_precision, int check_interval = 1000)
{
while (getAccuracy(desired_precision) < desired_accuracy)
{
for (int i = 0; i < check_interval; i++)
{
NN.feedForward(tset.inputs[i % tset.size]);
backpropagate(tset.outputs[i % tset.size]);
}
}
}
public override double Evaluate(double[] inputs)
{
NN.feedForward(inputs);
//Console.Write("Hidden\t: ");
//StdTest.WeightsTest.PrintHist(NN.hiddenNeurons);
//Console.WriteLine($"OUT: {NN.outputNeurons[0].ToString("N2")}");
return(NN.outputNeurons[0]);
}
public void TrainOne(double[] inputs, double[] desiredOutputs, double learningRate)
{
NN.feedForward(inputs);
backpropagate(desiredOutputs, learningRate);
}