/usr/include/shogun/kernel/SparseKernel.h is in libshogun-dev 1.1.0-4ubuntu2.
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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 | /*
* 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) 1999-2009 Soeren Sonnenburg
* Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
*/
#ifndef _SPARSEKERNEL_H___
#define _SPARSEKERNEL_H___
#include <shogun/kernel/Kernel.h>
#include <shogun/features/SparseFeatures.h>
namespace shogun
{
/** @brief Template class SparseKernel, is the base class of kernels working on sparse
* features.
*
* See e.g. the CSparseGaussianKernel for an example.
*/
template <class ST> class CSparseKernel : public CKernel
{
public:
/** constructor
*
* @param cachesize cache size
*/
CSparseKernel(int32_t cachesize) : CKernel(cachesize) {}
/** constructor
*
* @param l features for left-hand side
* @param r features for right-hand side
*/
CSparseKernel(CFeatures* l, CFeatures* r) : CKernel(10)
{
init(l, r);
}
/** 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)
{
CKernel::init(l,r);
ASSERT(l->get_feature_class()==C_SPARSE);
ASSERT(r->get_feature_class()==C_SPARSE);
ASSERT(l->get_feature_type()==this->get_feature_type());
ASSERT(r->get_feature_type()==this->get_feature_type());
if (((CSparseFeatures<ST>*) lhs)->get_num_features() != ((CSparseFeatures<ST>*) rhs)->get_num_features())
{
SG_ERROR( "train or test features #dimension mismatch (l:%d vs. r:%d)\n",
((CSparseFeatures<ST>*) lhs)->get_num_features(),((CSparseFeatures<ST>*)rhs)->get_num_features());
}
return true;
}
/** return feature class the kernel can deal with
*
* @return feature class SPARSE
*/
inline virtual EFeatureClass get_feature_class() { return C_SPARSE; }
/** return feature type the kernel can deal with
*
* @return templated feature type
*/
inline virtual EFeatureType get_feature_type();
/** Returns the name of the SGSerializable instance. It MUST BE
* the CLASS NAME without the prefixed `C'.
*
* @return name of the SGSerializable
*/
virtual const char* get_name() const {
return "SparseKernel"; }
/** return what type of kernel we are, e.g.
* Linear,Polynomial, Gaussian,...
*
* abstract base method
*
* @return kernel type
*/
virtual EKernelType get_kernel_type()=0;
};
template<> inline EFeatureType CSparseKernel<float64_t>::get_feature_type() { return F_DREAL; }
template<> inline EFeatureType CSparseKernel<uint64_t>::get_feature_type() { return F_ULONG; }
template<> inline EFeatureType CSparseKernel<int32_t>::get_feature_type() { return F_INT; }
template<> inline EFeatureType CSparseKernel<uint16_t>::get_feature_type() { return F_WORD; }
template<> inline EFeatureType CSparseKernel<int16_t>::get_feature_type() { return F_SHORT; }
template<> inline EFeatureType CSparseKernel<uint8_t>::get_feature_type() { return F_BYTE; }
template<> inline EFeatureType CSparseKernel<char>::get_feature_type() { return F_CHAR; }
}
#endif /* _SPARSEKERNEL_H__ */
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