Exemplo n.º 1
0
        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);
        }
Exemplo n.º 2
0
        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);
        }