/usr/include/shogun/classifier/svm/gpdt.h is in libshogun-dev 1.1.0-4ubuntu2.
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The actual contents of the file can be viewed below.
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*** GPDT - Gradient Projection Decomposition Technique ***
******************************************************************************
*** ***
*** GPDT is a C++ software designed to train large-scale Support Vector ***
*** Machines for binary classification in both scalar and distributed ***
*** memory parallel environments. It uses the Joachims' problem ***
*** decomposition technique to split the whole quadratic programming (QP) ***
*** problem into a sequence of smaller QP subproblems, each one being ***
*** solved by a suitable gradient projection method (GPM). The presently ***
*** implemented GPMs are the Generalized Variable Projection Method ***
*** GVPM (T. Serafini, G. Zanghirati, L. Zanni, "Gradient Projection ***
*** Methods for Quadratic Programs and Applications in Training Support ***
*** Vector Machines"; Optim. Meth. Soft. 20, 2005, 353-378) and the ***
*** Dai-Fletcher Method DFGPM (Y. Dai and R. Fletcher,"New Algorithms for ***
*** Singly Linear Constrained Quadratic Programs Subject to Lower and ***
*** Upper Bounds"; Math. Prog. to appear). ***
*** ***
*** Authors: ***
*** Thomas Serafini, Luca Zanni ***
*** Dept. of Mathematics, University of Modena and Reggio Emilia - ITALY ***
*** serafini.thomas@unimo.it, zanni.luca@unimo.it ***
*** Gaetano Zanghirati ***
*** Dept. of Mathematics, University of Ferrara - ITALY ***
*** g.zanghirati@unife.it ***
*** ***
*** Software homepage: http://dm.unife.it/gpdt ***
*** ***
*** This work is supported by the Italian FIRB Projects ***
*** 'Statistical Learning: Theory, Algorithms and Applications' ***
*** (grant RBAU01877P), http://slipguru.disi.unige.it/ASTA ***
*** and ***
*** 'Parallel Algorithms and Numerical Nonlinear Optimization' ***
*** (grant RBAU01JYPN), http://dm.unife.it/pn2o ***
*** ***
*** Copyright (C) 2004 by T. Serafini, G. Zanghirati, L. Zanni. ***
*** ***
*** COPYRIGHT NOTIFICATION ***
*** ***
*** Permission to copy and modify this software and its documentation ***
*** for internal research use is granted, provided that this notice is ***
*** retained thereon and on all copies or modifications. The authors and ***
*** their respective Universities makes no representations as to the ***
*** suitability and operability of this software for any purpose. It is ***
*** provided "as is" without express or implied warranty. ***
*** Use of this software for commercial purposes is expressly prohibited ***
*** without contacting the authors. ***
*** ***
*** This program 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 3 of the License, or ***
*** (at your option) any later version. ***
*** ***
*** This program 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 this program; if not, write to the Free Software ***
*** Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. ***
*** ***
*** File: gpdt.h ***
*** Type: scalar ***
*** Version: 1.0 ***
*** Date: October, 2005 ***
*** Revision: 1 ***
*** ***
******************************************************************************/
#include <shogun/kernel/Kernel.h>
#ifndef DOXYGEN_SHOULD_SKIP_THIS
namespace shogun
{
#define MAXLENGTH 256
#define cachetype KERNELCACHE_ELEM
#define EPS_SV 1.0e-9 /* precision for multipliers */
enum {
SOLVER_VPM = 0,
SOLVER_FLETCHER = 1
};
/** s kernel */
class sKernel
{
public:
/** kernel type */
int32_t ker_type;
/** lx */
int32_t *lx;
/** ix */
int32_t **ix;
/** x */
float32_t **x;
/** nor */
float64_t *nor;
/** sigma */
float64_t sigma;
/** degree */
float64_t degree;
/** normalization factor */
float64_t norm;
/** c poly */
float64_t c_poly;
/** kernel evaluations */
float64_t KernelEvaluations;
/** call kernel fun
*
* @param i
* @param j
* @return something floaty
*/
float64_t (sKernel::*kernel_fun)(int32_t i, int32_t j);
/** constructor
*
* @param k kernel
* @param ell ell
*/
sKernel (shogun::CKernel* k, int32_t ell);
~sKernel();
/** set data
*
* @param x_ new x
* @param ix_ new ix
* @param lx_ new lx
* @param ell new ell
* @param dim dim
*/
void SetData(
float32_t **x_, int32_t **ix_, int32_t *lx_, int32_t ell, int32_t dim);
/** set subproblem
*
* @param ker kernel
* @param len len
* @param perm perm
*/
void SetSubproblem (sKernel* ker, int32_t len, int32_t *perm);
/** get an item from the kernel
*
* @param i index i
* @param j index j
* @return item from kernel at index i, j
*/
float64_t Get(int32_t i, int32_t j)
{
KernelEvaluations += 1.0F;
return kernel->kernel(i, j);
}
/** add something
*
* @param v v
* @param j j
* @param mul mul
*/
void Add (float64_t *v, int32_t j, float64_t mul);
/** prod something
*
* @param v v
* @param j j
* @return something floaty
*/
float64_t Prod (float64_t *v, int32_t j);
/** get kernel
*
* @return kernel
*/
inline CKernel* get_kernel()
{
return kernel;
}
private:
CKernel* kernel;
int32_t vauxRow;
int32_t IsSubproblem;
int32_t ell, dim;
float32_t *vaux;
float64_t dot (int32_t i, int32_t j);
};
void SplitParts (
int32_t n, int32_t part, int32_t parts, int32_t *dim, int32_t *off);
void SplitNum (int32_t n, int32_t *nloc, int32_t *noff);
}
#endif // DOXYGEN_SHOULD_SKIP_THIS
/******************************************************************************/
/*** End of gpdt.h file ***/
/******************************************************************************/
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