public void GaussianDynamicalTimeWarpingConstructorTest()
{
double[][] sequences =
{
new double[] // -1
{
0, 0, 0,
1, 1, 1,
2, 2, 2,
},
new double[] // -1
{
0, 1, 0,
0, 2, 0,
0, 3, 0
},
new double[] // +1
{
1, 1, 0,
1, 2, 0,
2, 1, 0,
},
new double[] // +1
{
0, 0, 1,
0, 0, 2,
0, 1, 3,
},
};
int[] outputs = { -1, -1, +1, +1 };
// Set the parameters of the kernel
double alpha = 0.85;
int innerVectorLength = 3;
// Create the kernel. Note that the input vector will be given out automatically
var kernel = new Gaussian<DynamicTimeWarping>(new DynamicTimeWarping(innerVectorLength, alpha));
// When using variable-length kernels, specify 0 as the input length.
var svm = new KernelSupportVectorMachine(kernel, 0);
// Create the Sequential Minimal Optimization as usual
var smo = new SequentialMinimalOptimization(svm, sequences, outputs);
smo.Complexity = 1.5;
double error = smo.Run();
// Computing the training values
var a0 = svm.Compute(sequences[0]);
var a1 = svm.Compute(sequences[1]);
var a2 = svm.Compute(sequences[2]);
var a3 = svm.Compute(sequences[3]);
Assert.AreEqual(-1, System.Math.Sign(a0));
Assert.AreEqual(-1, System.Math.Sign(a1));
Assert.AreEqual(+1, System.Math.Sign(a2));
Assert.AreEqual(+1, System.Math.Sign(a3));
// Computing a new testing value
double[] test =
{
1, 0, 1,
0, 0, 2,
0, 1, 3,
};
var a4 = svm.Compute(test);
Assert.AreEqual(+1, System.Math.Sign(a4));
}
