public NeuralNetwork(
ActivationFunction activationFunction,
double initialWeightsRange,
params int[] sizes
)
{
Sizes = sizes;
InputLayer = new InputLayer();
HiddenLayers = new HiddenLayer[sizes.Length - 2];
for (var i = 0; i < sizes.Length - 2; i++)
{
//var isLast = i == sizes.Length - 1;
HiddenLayers[i] = new HiddenLayer(
sizes[i],
sizes[i + 1],
activationFunction,
initialWeightsRange);
}
var length = sizes.Length;
OutputLayer = new OutputLayer(
sizes[length - 2],
sizes[length - 1],
activationFunction,
initialWeightsRange);
}
public new Vector <double> Compute(Vector <double> input)
{
input = InputLayer.Feedforward(input);
foreach (var layer in HiddenLayers)
{
input = layer.Feedforward(input);
}
var decision = OutputLayer.Feedforward(input);
return(decision);
}
