1 files changed, 0 insertions, 123 deletions
diff --git a/ml/dlib/dlib/test/probabilistic.cpp b/ml/dlib/dlib/test/probabilistic.cpp
deleted file mode 100644
index e8a24829a..000000000
--- a/ml/dlib/dlib/test/probabilistic.cpp
+++ /dev/null
@@ -1,123 +0,0 @@
-// Copyright (C) 2011  Davis E. King (davis@dlib.net)
-// License: Boost Software License   See LICENSE.txt for the full license.
-
-
-#include <dlib/matrix.h>
-#include <sstream>
-#include <string>
-#include <cstdlib>
-#include <ctime>
-#include <vector>
-#include "../stl_checked.h"
-#include "../array.h"
-#include "../rand.h"
-#include "checkerboard.h"
-#include <dlib/statistics.h>
-
-#include "tester.h"
-#include <dlib/svm_threaded.h>
-
-
-namespace  
-{
-
-    using namespace test;
-    using namespace dlib;
-    using namespace std;
-
-    logger dlog("test.probabilistic");
-
-// ----------------------------------------------------------------------------------------
-
-    class test_probabilistic : public tester
-    {
-    public:
-        test_probabilistic (
-        ) :
-            tester ("test_probabilistic",
-                    "Runs tests on the probabilistic trainer adapter.")
-        {}
-
-        void perform_test (
-        )
-        {
-            print_spinner();
-
-
-            typedef double scalar_type;
-            typedef matrix<scalar_type,2,1> sample_type;
-
-            std::vector<sample_type> x;
-            std::vector<matrix<double,0,1> > x_linearized;
-            std::vector<scalar_type> y;
-
-            get_checkerboard_problem(x,y, 1000, 2);
-
-            random_subset_selector<sample_type> rx;
-            random_subset_selector<scalar_type> ry;
-            rx.set_max_size(x.size());
-            ry.set_max_size(x.size());
-
-            dlog << LINFO << "pos labels: "<< sum(mat(y) == +1);
-            dlog << LINFO << "neg labels: "<< sum(mat(y) == -1);
-
-            for (unsigned long i = 0; i < x.size(); ++i)
-            {
-                rx.add(x[i]);
-                ry.add(y[i]);
-            }
-
-            const scalar_type gamma = 2.0;
-
-            typedef radial_basis_kernel<sample_type> kernel_type;
-
-            krr_trainer<kernel_type> krr_trainer;
-            krr_trainer.use_classification_loss_for_loo_cv();
-            krr_trainer.set_kernel(kernel_type(gamma));
-            krr_trainer.set_basis(randomly_subsample(x, 100));
-            probabilistic_decision_function<kernel_type> df;
-
-            dlog << LINFO << "cross validation: " << cross_validate_trainer(krr_trainer, rx,ry, 4);
-            print_spinner();
-
-            running_stats<scalar_type> rs_pos, rs_neg;
-
-            print_spinner();
-            df = probabilistic(krr_trainer,3).train(x, y);
-            for (unsigned long i = 0; i < x.size(); ++i)
-            {
-                if (y[i] > 0)
-                    rs_pos.add(df(x[i]));
-                else
-                    rs_neg.add(df(x[i]));
-            }
-            dlog << LINFO << "rs_pos.mean(): "<< rs_pos.mean();
-            dlog << LINFO << "rs_neg.mean(): "<< rs_neg.mean();
-            DLIB_TEST_MSG(rs_pos.mean() > 0.95, rs_pos.mean());
-            DLIB_TEST_MSG(rs_neg.mean() < 0.05, rs_neg.mean());
-            rs_pos.clear();
-            rs_neg.clear();
-
-
-            print_spinner();
-            df = probabilistic(krr_trainer,3).train(rx, ry);
-            for (unsigned long i = 0; i < x.size(); ++i)
-            {
-                if (y[i] > 0)
-                    rs_pos.add(df(x[i]));
-                else
-                    rs_neg.add(df(x[i]));
-            }
-            dlog << LINFO << "rs_pos.mean(): "<< rs_pos.mean();
-            dlog << LINFO << "rs_neg.mean(): "<< rs_neg.mean();
-            DLIB_TEST_MSG(rs_pos.mean() > 0.95, rs_pos.mean());
-            DLIB_TEST_MSG(rs_neg.mean() < 0.05, rs_neg.mean());
-            rs_pos.clear();
-            rs_neg.clear();
-
-        }
-    } a;
-
-}
-
-