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// Copyright (C) 2002 Ronan Collobert (collober@iro.umontreal.ca)
//
//
// This file is part of Torch. Release II.
// [The Ultimate Machine Learning Library]
//
// Torch is free software; you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation; either version 2 of the License, or
// (at your option) any later version.
//
// Torch is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with Torch; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#ifndef SVM_CLASSIFICATION_INC
#define SVM_CLASSIFICATION_INC
#include "SVM.h"
namespace Torch {
/** SVM in classification.
Try to find the hyperplane $w.x+b = 0$
as
$(w,b)$ minimize $0.5*||w||^2 + \sum_j C_j |1- y_j*(w.x_j+b)|_+$
(where $|x|_+ = x$ if $x > 0$, else $0$)
(in fact, we use a #kernel# instead of a dot product)
The $C_j$ coefficients are given in #C_# when you
call the constructor. If this one is NULL, then
the value given by the "C" option is used for
all $C_j$.
(The size of #C_# \emph{must be} #data->n_real_examples#)
@author Ronan Collobert (collober@iro.umontreal.ca)
*/
class SVMClassification : public SVM
{
public:
real *Cuser;
//-----
///
SVMClassification(Kernel *kernel_, real *C_=NULL);
//-----
virtual void checkSupportVectors();
virtual void reset();
virtual ~SVMClassification();
};
}
#endif
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