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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_INC
#define SVM_INC
#include "QCMachine.h"
#include "Kernel.h"
#include "DataSet.h"
namespace Torch {
/** Support Vector Machine.
The Q matrix of #QCMachine# is in this case
$q_{ij} = k(x_i, x_j)$, where $k$ is a kernel
and $x_i$ is the i-th example of #data#/
The goal is to looking for the #alpha# and #b#
which are the best in a SVM-sense.
The learning function is
$f(x) = \sum_j y_j alpha_j k(x_i, x) + b$
Options:
\begin{tabular}{lcll}
"C" & real & trade off between the weight decay and the error & [100]
\end{tabular}
@author Ronan Collobert (collober@iro.umontreal.ca)
*/
class SVM : public QCMachine
{
public:
/** The dataset associated to the SVM.
(Given by the kernel)
*/
DataSet *data;
/// The kernel associated to the SVM.
Kernel *kernel;
/// The "C" constant.
real C_cst;
///
real b;
/// The support vectors
int *support_vectors;
/// The real index of the support vectors in the dataset
int *real_index;
/// The number of support vectors
int n_support_vectors;
/// The number of support vectors which are at the bound "C"
int n_support_vectors_bound;
//-----
///
SVM(Kernel *kernel_);
/// Computes the #b#.
bool bCompute();
//-----
virtual void init();
virtual void forward(List *inputs);
virtual void loadFILE(FILE *file);
virtual void saveFILE(FILE *file);
virtual ~SVM();
};
}
#endif
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