/usr/include/shogun/kernel/ExponentialKernel.h is in libshogun-dev 3.2.0-7.3build4.
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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 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 | /*
* 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.
*
* Gaussian Kernel used as template, attribution:
* Written (W) 1999-2010 Soeren Sonnenburg
* Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
* Copyright (C) 2010 Berlin Institute of Technology
*
* Slightly edited by Justin Patera 2011
*/
#ifndef _EXPONENTIALKERNEL_H___
#define _EXPONENTIALKERNEL_H___
#include <shogun/lib/common.h>
#include <shogun/kernel/DotKernel.h>
#include <shogun/features/DotFeatures.h>
#include <shogun/distance/Distance.h>
namespace shogun
{
class CDotFeatures;
/** @brief The Exponential Kernel, closely related to the Gaussian Kernel
* computed on CDotFeatures.
*
* It is computed as
*
* \f[
* k({\bf x},{\bf x'})= exp(-\frac{||{\bf x}-{\bf x'}||}{\tau})
* \f]
*
* where \f$\tau\f$ is the kernel width.
*/
class CExponentialKernel: public CDotKernel
{
public:
/** default constructor
*
*/
CExponentialKernel();
/** constructor
*
* @param l features of left-hand side
* @param r features of right-hand side
* @param width width
* @param distance distance to be used
* @param size cache size
*/
CExponentialKernel(CDotFeatures* l, CDotFeatures* r,
float64_t width, CDistance* distance, int32_t size);
/** destructor */
virtual ~CExponentialKernel();
/** initialize kernel
*
* @param l features of left-hand side
* @param r features of right-hand side
* @return if initializing was successful
*/
virtual bool init(CFeatures* l, CFeatures* r);
/** clean up kernel */
virtual void cleanup();
/** return what type of kernel we are
*
* @return kernel type EXPONENTIAL
*/
virtual EKernelType get_kernel_type() { return K_EXPONENTIAL; }
/** return the kernel's name
*
* @return name Exponential
*/
virtual const char* get_name() const { return "ExponentialKernel"; }
/** return the kernel's width
*
* @return kernel width
*/
virtual float64_t get_width() const
{
return m_width;
}
protected:
/** compute kernel function for features a and b
* idx_{a,b} denote the index of the feature vectors
* in the corresponding feature object
*
* @param idx_a index a
* @param idx_b index b
* @return computed kernel function at indices a,b
*/
virtual float64_t compute(int32_t idx_a, int32_t idx_b);
/** Can (optionally) be overridden to post-initialize some
* member variables which are not PARAMETER::ADD'ed. Make
* sure that at first the overridden method
* BASE_CLASS::LOAD_SERIALIZABLE_POST is called.
*
* @exception ShogunException Will be thrown if an error
* occurres.
*/
virtual void load_serializable_post() throw (ShogunException);
private:
void init();
protected:
/** distance **/
CDistance* m_distance;
/** width */
float64_t m_width;
};
}
#endif /* _EXPONENTIALKERNEL_H__ */
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