// 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 //
///////////////////////////////////////////////////////////////////////////
/*
- This class is mostly able to learn a classifier from a SampleSet and
- to provide a scalar response on any test sample. Additional methods
- are required for persistence and select the possibly very few used
- features.
+ This class is almost purely virtual. It represents a classifier that
+ can be trained from a SampleSet and able to provide a scalar
+ response on any test sample. Additional methods are required for
+ persistence and select the possibly very few used features.
*/