public CacheUnorderedNeuralVectorProvider(IUnorderedNeuralVectorsProvider baseProvider, ObjectCache cache = null)
{
Contract.Requires(baseProvider != null);
BaseProvider = baseProvider;
this.cache = cache ?? MemoryCache.Default;
}
public static void TestNetwork(NeuralNetwork network, IUnorderedNeuralVectorsProvider validationProvider)
{
Contract.Requires(network != null);
var prov = (FullSampleProvider)validationProvider;
if (validationVectors == null) validationVectors = prov.GetAllVectors().ToList();
var clone = network.Clone();
Task.Factory.StartNew(() =>
{
var reset = clone.GetReset();
int fnCount = 0;
int fpCount = 0;
int okCount = 0;
int count = 0;
foreach (var vectors in validationVectors)
{
bool isDetectable = false;
foreach (var vector in vectors)
{
for (int idx = 0; idx < vector.InputVector.Length; idx++)
{
clone.InputInterface[idx] = vector.InputVector[idx].Value;
}
for (int i = 0; i < vector.NumberOfIterations; i++)
{
clone.Iteration();
}
if (vector.DesiredOutputVector[0] != null)
{
isDetectable = vector.DesiredOutputVector[0].Value > 0.0;
}
}
double detectedOutput = clone.OutputInterface[0];
bool isDetectedByNetwork = detectedOutput > 0.0;
if (isDetectedByNetwork == isDetectable)
{
okCount++;
}
else
{
if (isDetectedByNetwork)
{
fpCount++;
}
else
{
fnCount++;
}
}
count++;
reset.Reset();
}
double percent = ((double)okCount / count) * 100.0;
var result = new TestResult(percent, fnCount, fpCount);
Console.WriteLine(result);
});
}