public FeedforwardNeuronalNetworkResult <double> Predict(double[] inputValues)
{
var classifier = neuronalNetwork.Classify(inputValues);
FeedforwardNeuronalNetworkResult <double> feedforwardNeuronalNetworkResult =
new FeedforwardNeuronalNetworkResult <double>();
feedforwardNeuronalNetworkResult.OutputValues = classifier;
feedforwardNeuronalNetworkResult.PredictedValue = classifier[0];
return(feedforwardNeuronalNetworkResult);
}
public FeedforwardNeuronalNetworkResult <double> Classify(double[] inputValues)
{
var classifier = neuronalNetwork.Classify(inputValues);
FeedforwardNeuronalNetworkResult <double> feedforwardNeuronalNetworkResult = new FeedforwardNeuronalNetworkResult <double>();
feedforwardNeuronalNetworkResult.OutputValues = classifier;
for (int i = 0; i < classifier.Length; i++)
{
var actualResult = classifier[i];
if (feedforwardNeuronalNetworkResult.MaxValue < actualResult)
{
feedforwardNeuronalNetworkResult.MaxValue = actualResult;
feedforwardNeuronalNetworkResult.MaxValueOutputPosition = i;
}
}
return(feedforwardNeuronalNetworkResult);
}
