public void TestRandomNormalInitialization()
{
var initialization = Initializations.RandomNormal();
initialization.SetSeed(0);
var initializedMatrix = initialization.Initialize(2, 2);
var expectedMatrix = Matrix <double> .Build.Random(2, 2, new Normal(new Random(0)));
Console.WriteLine(initializedMatrix);
Console.WriteLine(expectedMatrix);
Assert.AreEqual(initializedMatrix, expectedMatrix);
}
static void Main(string[] args)
{
var X = Matrix <double> .Build.Random(5, 100);
var Y = Matrix <double> .Build.Random(1, 100);
var test = Matrix <double> .Build.Random(5, 1);
var model = new DeepCat();
model.Add(new Dense(5, Activations.Relu(), weightInitializer: Initializations.RandomNormal()));
model.Add(new Dense(5, Activations.Relu(), weightInitializer: Initializations.RandomNormal()));
model.Add(new Dense(1, Activations.Sigmoid()));
model.Compile(X.RowCount, LossFunctions.CrossEntropy(), Optimizers.GradientDescent(0.002));
model.Fit(X, Y, 100);
model.Predict(test);
var x = 1;
}
