public void ComputeTest3()
{
// Example AND problem
double[][] inputs =
{
new double[] { 0, 0 }, // 0 and 0: 0 (label -1)
new double[] { 0, 1 }, // 0 and 1: 0 (label -1)
new double[] { 1, 0 }, // 1 and 0: 0 (label -1)
new double[] { 1, 1 } // 1 and 1: 1 (label +1)
};
// Dichotomy SVM outputs should be given as [-1;+1]
int[] labels =
{
// 0, 0, 0, 1
-1, -1, -1, 1
};
// Create a Support Vector Machine for the given inputs
KernelSupportVectorMachine machine = new KernelSupportVectorMachine(new Linear(), inputs[0].Length);
// Instantiate a new learning algorithm for SVMs
SequentialMinimalOptimization smo = new SequentialMinimalOptimization(machine, inputs, labels);
// Set up the learning algorithm
smo.Complexity = 100000.0;
// Run
double error = smo.Run();
Assert.AreEqual(-1, Math.Sign(machine.Compute(inputs[0])));
Assert.AreEqual(-1, Math.Sign(machine.Compute(inputs[1])));
Assert.AreEqual(-1, Math.Sign(machine.Compute(inputs[2])));
Assert.AreEqual(+1, Math.Sign(machine.Compute(inputs[3])));
Assert.AreEqual(error, 0);
Assert.AreEqual(-3.0, machine.Threshold);
Assert.AreEqual(4, machine.Weights[0]);
Assert.AreEqual(-2, machine.Weights[1]);
Assert.AreEqual(-2, machine.Weights[2]);
}