//!
private void RandomizeWeights()
{
var rnd = new Random();
//distribute -0.5 to 0.5.
WeightHiddenOutput.Initialize(() => rnd.NextDouble() - 0.5);
WeightInputHidden.Initialize(() => rnd.NextDouble() - 0.5);
}
public void Train(double[] inputs, double[] targets)
{
var inputSignals = ConvertToMatrix(inputs);
var targetSignals = ConvertToMatrix(targets);
var hiddenOutputs = Sigmoid(WeightInputHidden * inputSignals);
var finalOutputs = Sigmoid(WeightHiddenOutput * hiddenOutputs);
var outputErrors = targetSignals - finalOutputs;
var hiddenErrors = WeightHiddenOutput.Transpose() * outputErrors;
WeightHiddenOutput += LearningRate * outputErrors * finalOutputs * (1.0 - finalOutputs) * hiddenOutputs.Transpose();
WeightInputHidden += LearningRate * hiddenErrors * hiddenOutputs * (1.0 - hiddenOutputs) * inputSignals.Transpose();
}