void AddRegularizationL1(NeuralNetAccessor costFunctionGradient, float regularizationRate)
{
for (int layer = 0; layer < costFunctionGradient.NumberOfLayers; layer++)
{
for (int node = 0; node < costFunctionGradient.NodesInLayer(layer); node++)
{
var costFunctionGradientWeights = costFunctionGradient.GetSigmoid(layer, node).Weights;
var neuralNetWeights = neuralNetAccessor.GetSigmoid(layer, node).Weights;
for (int i = 0; i < costFunctionGradientWeights.Length; i++)
{
costFunctionGradientWeights[i] += Mathf.Sign(neuralNetWeights[i]) * regularizationRate;
}
}
}
}
public void InitializeWeightsAndBiases()
{
SimpleRNG.SetSeedFromSystemTime();
for (int layer = 0; layer < neuralNetAccessor.NumberOfLayers; layer++)
{
for (int node = 0; node < neuralNetAccessor.NodesInLayer(layer); node++)
{
var sigmoid = neuralNetAccessor.GetSigmoid(layer, node);
sigmoid.Bias = (float)SimpleRNG.GetNormal(0, 1);
float standardDeviation = 1.0f / Mathf.Sqrt(sigmoid.Weights.Length);
for (int i = 0; i < sigmoid.Weights.Length; i++)
{
sigmoid.Weights[i] = (float)SimpleRNG.GetNormal(0, standardDeviation);
}
}
}
}
