/usr/include/shogun/kernel/LinearARDKernel.h is in libshogun-dev 3.1.1-1.
This file is owned by root:root, with mode 0o644.
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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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 | /*
* 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.
*
* (W) 2012 Jacob Walker
*
* Adapted from WeightedDegreeRBFKernel.h
*/
#ifndef LINEARARDKERNEL_H_
#define LINEARARDKERNEL_H_
#include <shogun/lib/common.h>
#include <shogun/kernel/DotKernel.h>
#include <shogun/features/DenseFeatures.h>
namespace shogun
{
/** @brief Linear Kernel with Automatic Relevance Detection */
class CLinearARDKernel: public CDotKernel
{
public:
/** default constructor */
CLinearARDKernel();
/** constructor
*
* @param size cache size
*/
CLinearARDKernel(int32_t size);
/** constructor
*
* @param l features of left-hand side
* @param r features of right-hand side
* @param size cache size
*/
CLinearARDKernel(CDenseFeatures<float64_t>* l, CDenseFeatures<float64_t>* r,
int32_t size=10);
virtual ~CLinearARDKernel();
/** 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);
/** return what type of kernel we are
*
* @return kernel type LINEARARD
*/
virtual EKernelType get_kernel_type() { return K_LINEARARD; }
/** return the kernel's name
*
* @return name LinearARDKernel
*/
virtual const char* get_name() const { return "LinearARDKernel"; }
/** return feature class the kernel can deal with
*
* @return feature class DENSE
*/
virtual EFeatureClass get_feature_class() { return C_DENSE; }
/** return feature type the kernel can deal with
*
* @return float64_t feature type
*/
virtual EFeatureType get_feature_type() { return F_DREAL; }
/** set weight of particular feature/dimension
*
* @param w weight to set
* @param i index of feature
*/
virtual void set_weight(float64_t w, index_t i);
/** get weight of particular feature/dimension
*
* @param i index of feature
*
* @return weight of feature
*/
virtual float64_t get_weight(index_t i);
/** @return Current feature/dimension weights */
virtual SGVector<float64_t> get_weights() { return m_weights; }
/** setter for feature/dimension weights
*
* @param weights weights to set
*/
virtual void set_weights(SGVector<float64_t> weights) { m_weights=weights; }
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);
/** init feature weights
*
* @return if initialization was successful
*/
void init_ft_weights();
/** return derivative with respect to specified parameter
*
* @param param the parameter
* @param index the index of the element if parameter is a vector
*
* @return gradient with respect to parameter
*/
virtual SGMatrix<float64_t> get_parameter_gradient(const TParameter* param,
index_t index=-1);
private:
void init();
protected:
/** weights */
SGVector<float64_t> m_weights;
};
}
#endif /* LINEARARDKERNEL_H_ */
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