Accord.Tests.MachineLearning.SequentialMinimalOptimizationTest.FixedWeightsTest C# (CSharp) Method

        public void FixedWeightsTest()
        {
            var dataset = KernelSupportVectorMachineTest.training;
            var inputs = dataset.Submatrix(null, 0, 3);
            var labels = Accord.Math.Tools.Scale(0, 1, -1, 1, dataset.GetColumn(4)).ToInt32();

            var machine = new KernelSupportVectorMachine(
                Gaussian.Estimate(inputs), inputs[0].Length);

            var smo = new SequentialMinimalOptimization(machine, inputs, labels);

            smo.Complexity = 10;

            double error = smo.Run();

            Assert.AreEqual(0.19047619047619047, error);
            Assert.AreEqual(265.78327637381551, ((Gaussian)machine.Kernel).Sigma);
            Assert.AreEqual(29, machine.SupportVectors.Length);

            double[] expectedWeights =
            {
                1.65717694716503, 1.20005456611466, -5.70824245415995, 10,
                10, -2.38755497916487, 10, -8.15723436363058, 10, -10, 10,
                10, -0.188634936781317, -5.4354281009458, -8.48341139483265,
                -5.91105702760141, -5.71489190049223, 10, -2.37289205235858,
                -3.33031262413522, -1.97545116517677, 10, -10, -9.563186799279,
                -3.917941544845, -0.532584110773336, 4.81951847548326, 0.343668292727091,
                -4.34159482731336
            };

            //Assert.IsTrue(expectedWeights.IsEqual(machine.Weights, 1e-5));

            int[] actual = new int[labels.Length];
            for (int i = 0; i < actual.Length; i++)
                actual[i] = Math.Sign(machine.Compute(inputs[i]));

            ConfusionMatrix matrix = new ConfusionMatrix(actual, labels);

            Assert.AreEqual(8, matrix.FalseNegatives);
            Assert.AreEqual(0, matrix.FalsePositives);
            Assert.AreEqual(4, matrix.TruePositives);
            Assert.AreEqual(30, matrix.TrueNegatives);

            Assert.AreEqual(1 / 3.0, matrix.Sensitivity);
            Assert.AreEqual(1, matrix.Specificity);

            Assert.AreEqual(0.5, matrix.FScore);
            Assert.AreEqual(0.5129891760425771, matrix.MatthewsCorrelationCoefficient);
        }