Function test_dense

dlib/test/svm_c_linear.cpp:246–277

// ----------------------------------------------------------------------------------------

    void test_dense (
    )
    {
        print_spinner();
        dlog << LINFO << "test with dense vectors";
        std::vector<sample_type> samples;
        std::vector<double> labels;

        sample_type samp;

        get_simple_points(samples,labels);

        svm_c_linear_trainer<linear_kernel<sample_type> > trainer;
        trainer.set_c(1e4);
        //trainer.be_verbose();
        trainer.set_epsilon(1e-11);


        double obj;
        decision_function<linear_kernel<sample_type> > df = trainer.train(samples, labels, obj);
        dlog << LDEBUG << "obj: "<< obj;
        DLIB_TEST_MSG(abs(obj - 0.72222222222) < 1e-7, abs(obj - 0.72222222222));
        // There shouldn't be any margin violations since this dataset is so trivial.  So that means the objective
        // should be exactly the squared norm of the decision plane (times 0.5).
        DLIB_TEST_MSG(abs(length_squared(df.basis_vectors(0))*0.5 + df.b*df.b*0.5 - 0.72222222222) < 1e-7, 
                      length_squared(df.basis_vectors(0))*0.5 + df.b*df.b*0.5);

        DLIB_TEST(abs(df(samples[0]) - (-1)) < 1e-6);
        DLIB_TEST(abs(df(samples[1]) - (-1)) < 1e-6);
        DLIB_TEST(abs(df(samples[2]) - (1)) < 1e-6);
        DLIB_TEST(abs(df(samples[3]) - (1)) < 1e-6);
    }

// ----------------------------------------------------------------------------------------