Function test_rls

dlib/test/rls.cpp:24–172

    void test_rls()
    {
        dlib::rand rnd;

        running_stats<double> rs1, rs2, rs3, rs4, rs5;

        for (int k = 0; k < 2; ++k)
        {
            for (long num_vars = 1; num_vars < 4; ++num_vars)
            {
                print_spinner();
                for (long size = 1; size < 300; ++size)
                {
                    {
                        matrix<double> X = randm(size,num_vars,rnd);
                        matrix<double,0,1> Y = randm(size,1,rnd);


                        const double C = 1000;
                        const double forget_factor = 1.0;
                        rls r(forget_factor, C);
                        for (long i = 0; i < Y.size(); ++i)
                        {
                            r.train(trans(rowm(X,i)), Y(i));
                        }


                        matrix<double> w = pinv(1.0/C*identity_matrix<double>(X.nc()) + trans(X)*X)*trans(X)*Y;

                        rs1.add(length(r.get_w() - w));
                    }

                    {
                        matrix<double> X = randm(size,num_vars,rnd);
                        matrix<double,0,1> Y = randm(size,1,rnd);

                        matrix<double,0,1> G(size,1);

                        const double C = 10000;
                        const double forget_factor = 0.8;
                        rls r(forget_factor, C);
                        for (long i = 0; i < Y.size(); ++i)
                        {
                            r.train(trans(rowm(X,i)), Y(i));

                            G(i) = std::pow(forget_factor, i/2.0);
                        }

                        G = flipud(G);

                        X = diagm(G)*X;
                        Y = diagm(G)*Y;

                        matrix<double> w = pinv(1.0/C*identity_matrix<double>(X.nc()) + trans(X)*X)*trans(X)*Y;

                        rs5.add(length(r.get_w() - w));
                    }