public void HingeLoss_Loss_2()
{
var sut = new HingeLoss();
var targets = Matrix <float> .Build.Dense(3, 2, new float[] { 1f, 1f, 0f, 0f, 0f, 1, });
var predictions = Matrix <float> .Build.Dense(3, 2, new float[] { 0.9f, 0.9f, 0.1f, .1f, .1f, .9f });
var actual = sut.Loss(targets, predictions);
Assert.AreEqual(0.200000018, actual, 0.001);
}
public void HingeLoss_Loss()
{
// example from http://cs231n.github.io/linear-classify/#svmvssoftmax
var sut = new HingeLoss();
var targets = Matrix <float> .Build.Dense(1, 3, new float[] { 0, 0, 1 });
var predictions = Matrix <float> .Build.Dense(1, 3, new float[] { -2.85f, 0.86f, 0.28f });
var actual = sut.Loss(targets, predictions);
Assert.AreEqual(1.58, actual, 0.001);
}