public void LogisticRegression()
{
var X = Matrix <double> .Build.DenseOfArray(new double[, ] {
{ 1 }, { 2 }
});
var Y = Matrix <double> .Build.DenseOfArray(new double[, ] {
{ 1 }
});
var model = new DeepCat.DeepCat();
model.Add(new Dense(1, Activations.Sigmoid(), weightInitializer: Initializations.Fixed()));
model.Compile(X.RowCount, LossFunctions.CrossEntropy(), Optimizers.GradientDescent(0.02));
model.Fit(X, Y, 1);
var a = model.Predict(X);
a[0, 0] = Math.Round(a[0, 0], 8);
var expectedResult = Matrix <double> .Build.DenseOfArray(new double[, ] {
{ 0.59859297 }
});
Assert.AreEqual(a, expectedResult);
}
public void TestFixedInitialization()
{
var initialization = Initializations.Fixed();
var initializedMatrix = initialization.Initialize(2, 2);
var expectedMatrix = Matrix <double> .Build.DenseOfArray(new double[, ] {
{ 0.11, 0.12 }, { 0.21, 0.22 }
});
Assert.AreEqual(initializedMatrix, expectedMatrix);
}