Method test_lda

dlib/test/statistics.cpp:755–806

        }

        void test_lda ()
        {
            // This test makes sure we pick the right direction in a simple 2D -> 1D LDA
            typedef matrix<double,2,1> sample_type;

            std::vector<unsigned long> labels;
            std::vector<sample_type> samples;
            for (int i=0; i<4; i++)
            {
                sample_type s;
                s(0) = i;
                s(1) = i+1;
                samples.push_back(s);
                labels.push_back(1);       

                sample_type s1;
                s1(0) = i+1;
                s1(1) = i;
                samples.push_back(s1);      
                labels.push_back(2);       
            }

            matrix<double> X;  
            X.set_size(8,2);
            for (int i=0; i<8; i++){
                X(i,0) = samples[i](0);
                X(i,1) = samples[i](1);
            }  

            matrix<double,0,1> mean;   

            dlib::compute_lda_transform(X,mean,labels,1);

            std::vector<double> vals1, vals2;
            for (unsigned long i = 0; i < samples.size(); ++i)
            {
                double val = X*samples[i]-mean;
                if (i%2 == 0)
                    vals1.push_back(val);
                else
                    vals2.push_back(val);
                dlog << LINFO << "1D LDA output: " << val;
            }

            if (vals1[0] > vals2[0])
                swap(vals1, vals2);

            const double err = equal_error_rate(vals1, vals2).first;
            dlog << LINFO << "LDA ERR: " << err;
            DLIB_TEST(err == 0);
            DLIB_TEST(equal_error_rate(vals2, vals1).first == 1);
        }

        void test_equal_error_rate() 
        {