/usr/include/shogun/regression/svr/MKLRegression.h is in libshogun-dev 3.2.0-7.3build4.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | /*
* 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.
*
* Written (W) 2009 Soeren Sonnenburg
* Copyright (C) 2009 Fraunhofer Institute FIRST and Max-Planck-Society
*/
#ifndef __MKLREGRESSION_H__
#define __MKLREGRESSION_H__
#include <shogun/lib/common.h>
#include <shogun/classifier/mkl/MKL.h>
namespace shogun
{
/** @brief Multiple Kernel Learning for regression
*
* Performs support vector regression while learning kernel weights at the same
* time. Makes only sense if multiple kernels are used.
*
* \sa CMKL
*/
class CMKLRegression : public CMKL
{
public:
/** problem type */
MACHINE_PROBLEM_TYPE(PT_REGRESSION);
/** Constructor
*
* @param s SVM to use as constraint generator in MKL SILP
*/
CMKLRegression(CSVM* s=NULL);
/** Destructor
*/
virtual ~CMKLRegression();
/** compute beta independent term from objective, e.g., in 2-class MKL
* sum_i alpha_i etc
*/
virtual float64_t compute_sum_alpha();
/** @return object name */
virtual const char* get_name() const { return "MKLRegression"; }
protected:
/** check run before starting training (to e.g. check if labeling is
* two-class labeling in classification case
*/
virtual void init_training();
/** get classifier type
*
* @return classifier type MKL_REGRESSION
*/
virtual EMachineType get_classifier_type() { return CT_MKLREGRESSION; }
/** compute mkl dual objective
*
* @return computed dual objective
*/
virtual float64_t compute_mkl_dual_objective();
};
}
#endif //__MKLREGRESSION_H__
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