public WeightsAndBias Update(WeightsAndBias wb, Example example)
{
float DLoss = _loss.GetDerivative(Score(wb, example), example.Label);
if (_L2 == 0.0f)
{
wb.Weights.InplaceAddMultiply(-DLoss * _learningRate, example.Features);
}
else if (_L1 == 0.0f)
{
wb.Weights.InplaceAddMultiplyWithL2(_learningRate, -DLoss, _L2, example.Features);
}
else
{
wb.Weights.InplaceAddMultiplyWithL2AndL1(_learningRate, -DLoss, _L2, _L1, example.Features);
}
wb.Bias += -_learningRate * DLoss;
return(wb);
}
