public void IsTrainableByBackPropagation()
{
var net = MnistLearnerSigmoidNetBuilder.Build(15);
var trainingData = new MnistFilesReader(mnistRealDataDirectory).TrainingData.Take(200).Select(p => new LearningNeuralNetworks.V1.Pair <Image, byte>(p.Data, p.Label)).ToArray();
var scoreBeforeTraining = HitsScoredOnTestData(net, trainingData);
//
new BackPropagationWithGradientDescent().ApplyToBatches(net, trainingData, 10, 3, 100);
//
var scoreAfterTraining = HitsScoredOnTestData(net, trainingData);
Console.WriteLine("Scores before/after training: {0} / {1}", scoreBeforeTraining, scoreAfterTraining);
scoreAfterTraining.ShouldBeGreaterThan(scoreBeforeTraining);
}
void SetUpLoadedReader()
{
reader = (reader != null && reader.IsLoaded)
? reader
: new MnistFilesReader(mnistRealDataDirectory, 2).EnsureLoaded();
}
