public void CanBackLinear()
{
nf_linear.Run(vector_2);
DataVector result = nf_linear.BackPropagate(vector_2);
DataVector inputgradienttest = vector_2;
Assert.AreEqual(inputgradienttest, result);
}
public void CanBackSigmoid()
{
DataVector result = nf_sigmoid.Run(vector_2);
DataVector inputgradient = nf_sigmoid.BackPropagate(vector_2);
Vector <double> checkVector = Vector <double> .Build.DenseOfArray(
new double[] { sigmoidDerivative(vector_2[0], result[0]) * vector_2[0],
sigmoidDerivative(vector_2[1], result[1]) * vector_2[1] }
);
DataVector gradientCheck = new DataVector(checkVector);
Assert.AreEqual(gradientCheck, inputgradient);
}
public void CanBack()
{
DataVector result = nf_1.BackPropagate(vector_1);
Assert.AreEqual(vector_1, result);
}
