X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=loss_machine.h;h=96f0a59ebbdfc963d21abbd1b9b4ab83f636dc6c;hb=b8222ae1fb874f0783803f55e0bc4c4b9ffca8b2;hp=a293e8b71a9090bb2ed89fc1d31fafd7c819288d;hpb=d922ad61d35e9a6996730bec24b16f8bf7bc426c;p=folded-ctf.git

diff --git a/loss_machine.h b/loss_machine.h
index a293e8b..96f0a59 100644
--- a/loss_machine.h
+++ b/loss_machine.h
@@ -12,10 +12,20 @@
 // You should have received a copy of the GNU General Public License     //
 // along with this program. If not, see <http://www.gnu.org/licenses/>.  //
 //                                                                       //
-// Written by Francois Fleuret, (C) IDIAP                                //
+// Written by Francois Fleuret                                           //
+// (C) Idiap Research Institute                                          //
+//                                                                       //
 // Contact <francois.fleuret@idiap.ch> for comments & bug reports        //
 ///////////////////////////////////////////////////////////////////////////
 
+/*
+
+  A LossMachine provides all the methods necessary to do boosting with
+  a certain loss. Note that only the LOSS_EXPONENTIAL has been really
+  tested. Using the others may result in unexpected effects.
+
+ */
+
 #ifndef LOSS_MACHINE_H
 #define LOSS_MACHINE_H
 
@@ -38,14 +48,14 @@ public:
                           scalar_t *weak_learner_responses,
                           scalar_t *current_responses);
 
-  // This method returns in sample_nb_occurences[k] the number of time
-  // the example k was sampled, and in sample_responses[k] the
-  // consistent response so that the overall loss remains the same. If
-  // allow_duplicates is set to 1, all samples will have an identical
-  // response (i.e. weight), but some may have more than one
-  // occurence. On the contrary, if allow_duplicates is 0, samples
-  // will all have only one occurence (or zero) but the responses may
-  // vary to account for the multiple sampling.
+  /* This method returns in sample_nb_occurences[k] the number of time
+     the example k was sampled, and in sample_responses[k] the
+     consistent response so that the overall loss remains the same. If
+     allow_duplicates is set to 1, all samples will have an identical
+     response (i.e. weight), but some may have more than one
+     occurence. On the contrary, if allow_duplicates is 0, samples
+     will all have only one occurence (or zero) but the responses may
+     vary to account for the multiple sampling. */
 
   void subsample(int nb, scalar_t *labels, scalar_t *responses,
                  int nb_to_sample, int *sample_nb_occurences, scalar_t *sample_responses,