IKernel kernel = new DynamicTimeWarping(dimension);
        var machine = new MulticlassSupportVectorMachine(0, kernel, 2);
        // Create the Multi-class learning algorithm for the machine
        var teacher = new MulticlassSupportVectorLearning(machine, inputs.ToArray(), outputs.ToArray());
        // Configure the learning algorithm to use SMO to train the
        //  underlying SVMs in each of the binary class subproblems.
        teacher.Algorithm = (svm, classInputs, classOutputs, i, j) =>
            new SequentialMinimalOptimization(svm, classInputs, classOutputs)
            {
                Complexity = 1.5
            };
        // Run the learning algorithm
        double error = teacher.Run();