public void AddDataAfterEducate(NeuralNetworkObj neuralNetworkObj, Dictionary <double[], double[]> prepareData)
{
data.Add("#########################################");
data.Add("#########################################");
int id = 1;
foreach (var entity in prepareData)
{
double[] inputVector = entity.Key;
double[] expectedResultVector = entity.Value;
neuralNetworkObj.Clear();
neuralNetworkObj.SetInputVector(inputVector);
neuralNetworkObj.Process();
double[] resultVector = GetResultVector(neuralNetworkObj);
data.Add($"ID: {id}");
data.Add($"Epoch: {neuralNetworkObj.GetCountEpochPassed()} (After educate)");
data.Add($"Error: {this.errorMethod.GetError(expectedResultVector, resultVector).ToString()}");
data.Add("Expected Result:");
foreach (var item in expectedResultVector)
{
data.Add(item.ToString());
}
data.Add("Result:");
foreach (var item in resultVector)
{
data.Add(item.ToString());
}
data.Add("#########################################");
id++;
}
}
private double[] GetResultVector(NeuralNetworkObj neuralNetworkObj, double[] inputVector)
{
double[] result = new double[neuralNetworkObj.GetLastLayer().GetCountNeurons()];
neuralNetworkObj.Clear();
neuralNetworkObj.SetInputVector(inputVector);
neuralNetworkObj.Process();
List <NeuralNetwork.NeuronObj> neurons = neuralNetworkObj.GetLastLayer().GetListNeurons();
for (int i = 0; i < neurons.Count; i++)
{
result[i] = neurons[i].GetOutputData();
}
return(result);
}
public int GetNumberFromImgVector(double[] inputVector)
{
if (inputVector.Length != this.countNeuronsInFirstLayer)
{
throw new Exception("Invalid input vector length.");
}
NeuralNetworkObj neuralNetworkObj = this.GetNeuralNetwork();
neuralNetworkObj.Clear();
neuralNetworkObj.SetInputVector(inputVector);
neuralNetworkObj.Process();
foreach (NeuronObj neuron in neuralNetworkObj.GetLastLayer().GetListNeurons())
{
if (neuron.GetOutputData() > MINIMUM_OUTPUT_DATA_FOR_SUCCESS_RESULT)
{
return(neuron.Id);
}
}
return(-1);
}