public void KernelTest1()
{
var dataset = SequentialMinimalOptimizationTest.GetYingYang();
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], 1e-8);
Assert.AreEqual(w1[1], w2[1], 1e-8);
Assert.AreEqual(w1[2], w2[2], 1e-8);
}
