/// <summary>
/// Tests the network.
/// </summary>
/// <param name="network">The network.</param>
public void TestNetwork(TeachableNetwork network)
{
int passedTests = 0;
int failedTests = 0;
foreach (TestingSet testingSet in TestingCollection.Values)
{
network.ComputeNetworkResponse(testingSet.Input);
double[] response = network.GetResponse();
double max = -1;
int index = 0;
for (int i = 0; i < response.Length; i++)
{
if (response[i] > max)
{
max = response[i];
index = i;
}
}
if (index == testingSet.Value)
{
Console.WriteLine("Test passed: {0} recognized.", testingSet.Value);
passedTests++;
}
else
{
Console.WriteLine("Test failed: {0} recognized instead {1}.", index, testingSet.Value);
failedTests++;
}
}
Console.WriteLine("All passed tests: {0}.", passedTests);
Console.WriteLine("All failed tests: {0}.", failedTests);
}
/// <summary>
/// Teaches the network.
/// </summary>
/// <param name="network">The network.</param>
public void TeachNetwork(TeachableNetwork network)
{
int era = 0;
double errorForWholeEra = 0;
int currentIterationCount = 0;
do
{
era++;
errorForWholeEra = 0;
TrainingCollection.Values.Shuffle();
foreach (var trainingSet in TrainingCollection.Values)
{
currentIterationCount++;
network.LearnSomething(trainingSet.Input, trainingSet.Response);
}
TrainingCollection.Values.Shuffle();
errorForWholeEra = GiveErrorForWholeEra(network);
}
while(!Stop(errorForWholeEra, era, currentIterationCount));
}
/// <summary>
/// Prepares the network.
/// </summary>
private void PrepareNetwork()
{
int[] neurons = new int[3];
neurons[0] = WIDTH_FOR_BITMAP * HEIGHTH_FOR_BITMAP;
neurons[1] = 88;
neurons[2] = 10;
double beta = 2.0;
double eta = 0.2;
double momentum = 0.3;
_network = new TeachableNetwork(neurons, beta, eta, momentum);
TrainingCollection trainingData = TrainingCollection.LoadUserData(_path);
double minDelta = 0.001; // 0.005
int maxAge = 1000;
int maxIteration = 10000000;
_teacherForNetwork = new Teacher(trainingData, minDelta, maxAge, maxIteration);
}
