public void ExponentialCostTest()
{
var rnd = new Random();
var tao = rnd.NextDouble() * 10;
var error = 0.0;
var actual = new Matrix(4, 1);
actual.InRandomize();
var expected = new Matrix(4, 1);
expected.InRandomize();
for (var i = 0; i < actual.Rows; i++)
{
for (var j = 0; j < actual.Columns; j++)
{
error += Math.Pow(actual[i, j] - expected[i, j], 2);
}
}
error /= tao;
error = Math.Exp(error);
error *= tao;
var cost = new ExponentialCostKernel(new ExponentionalCost(tao));
var calculatedError = cost.Forward(actual, expected);
Assert.IsTrue(Math.Abs(error - calculatedError) < 0.01f, "Exponential Cost successful");
}
public void ExponentialCostPrimeTest()
{
var rnd = new Random();
var tao = rnd.NextDouble() * 10;
var error = 0.0;
var actual = new Matrix(4, 1);
actual.InRandomize();
var expected = new Matrix(4, 1);
expected.InRandomize();
for (var i = 0; i < actual.Rows; i++)
{
for (var j = 0; j < actual.Columns; j++)
{
error += Math.Pow(actual[i, j] - expected[i, j], 2);
}
}
error /= tao;
error = Math.Exp(error);
error *= tao;
var gradMatrix = actual.Duplicate();
for (var i = 0; i < actual.Rows; i++)
{
for (var j = 0; j < actual.Columns; j++)
{
gradMatrix[i, j] = (actual[i, j] - expected[i, j]) * error;
}
}
var cost = new ExponentialCostKernel(new ExponentionalCost(tao));
var calculatedMatrix = cost.Backward(actual, expected);
Assert.IsTrue(gradMatrix == calculatedMatrix, "Exponential Cost Derivative successful");
}
