Accord.Tests.MachineLearning.ProbabilisticCoordinateDescentTest.KernelTest1 C# (CSharp) Метод

        public void KernelTest1()
        {
            var dataset = SequentialMinimalOptimizationTest.yinyang;
            double[][] inputs = dataset.Submatrix(null, 0, 1).ToJagged();
            int[] labels = dataset.GetColumn(2).ToInt32();

            double e1, e2;
            double[] w1, w2;

            {
                Accord.Math.Random.Generator.Seed = 0;

                var svm = new SupportVectorMachine(inputs: 2);
                var teacher = new ProbabilisticCoordinateDescent(svm, inputs, labels);

                teacher.Tolerance = 1e-10;
                teacher.Complexity = 1e+10;

                e1 = teacher.Run();
                w1 = svm.ToWeights();
            }

            {
                Accord.Math.Random.Generator.Seed = 0;

                var svm = new KernelSupportVectorMachine(new Linear(0), inputs: 2);
                var teacher = new ProbabilisticCoordinateDescent(svm, inputs, labels);

                teacher.Tolerance = 1e-10;
                teacher.Complexity = 1e+10;

                e2 = teacher.Run();
                w2 = svm.ToWeights();
            }

            Assert.AreEqual(e1, e2);
            Assert.AreEqual(w1.Length, w2.Length);
            Assert.AreEqual(w1[0], w2[0]);
            Assert.AreEqual(w1[1], w2[1]);
            Assert.AreEqual(w1[2], w2[2]);
        }