12 #ifndef __GUIKERNEL__H
13 #define __GUIKERNEL__H
78 bool source_is_diag,
bool dest_is_diag);
81 int32_t size=10,
float64_t width=1, int32_t max_shift=0,
82 int32_t shift_step=1);
92 int32_t size,
float64_t* km, int32_t rows, int32_t cols);
95 int32_t size=10, int32_t degree=2,
bool inhomogene=
false,
99 int32_t size=10, int32_t degree=2,
bool inhomogene=
false,
100 bool normalize=
true);
106 int32_t size=10, int32_t length=3, int32_t inner_degree=3,
110 int32_t size=10, int32_t order=3, int32_t max_mismatch=1,
111 bool use_normalization=
true, int32_t mkl_stepsize=1,
112 bool block_computation=
true, int32_t single_degree=-1);
115 int32_t size=10, int32_t order=3, int32_t max_mismatch=1,
116 int32_t length=0, int32_t center=0,
float64_t step=1);
119 int32_t size=10, int32_t order=3, int32_t max_mismatch=1,
120 int32_t* shifts=NULL, int32_t length=0, int32_t mkl_stepsize=1,
124 int32_t size=10, int32_t order=3, int32_t max_mismatch=1,
125 int32_t* shifts=NULL, int32_t length=0,
bool use_normalization=
true);
138 int32_t size=10,
bool use_sign=
false,
char* norm_str=NULL,
142 int32_t size=10, int32_t d=3,
bool normalize=
true);
145 int32_t size=10, int32_t degree=2,
bool inhomogene=
false,
146 bool normalize=
true);
149 int32_t size=10, int32_t degree=2,
bool inhomogene=
false,
150 bool normalize=
true);
169 int32_t size=10,
bool append_subkernel_weights=
false);
172 virtual const char*
get_name()
const {
return "GUIKernel"; }
183 float64_t* get_weights(int32_t order, int32_t max_mismatch);
CKernel * create_spectrummismatchrbf(int32_t size=10, float64_t *AA_matrix=NULL, int32_t nr=128, int32_t nc=128, int32_t max_mismatch=1, int32_t degree=1, float64_t width=1)
CKernel * create_linear(int32_t size=10, float64_t scale=-1)
CKernel * create_weighteddegreepositionstring(int32_t size=10, int32_t order=3, int32_t max_mismatch=1, int32_t length=0, int32_t center=0, float64_t step=1)
CKernel * create_sparsepoly(int32_t size=10, int32_t degree=2, bool inhomogene=false, bool normalize=true)
bool resize_kernel_cache(int32_t size)
CKernel * create_histogramword(int32_t size=10)
CKernel * create_commstring(int32_t size=10, bool use_sign=false, char *norm_str=NULL, EKernelType ktype=K_WEIGHTEDCOMMWORDSTRING)
CKernel * create_polymatchwordstring(int32_t size=10, int32_t degree=2, bool inhomogene=false, bool normalize=true)
CKernel * create_sparselinear(int32_t size=10, float64_t scale=-1)
CKernel * create_fixeddegreestring(int32_t size=10, int32_t d=3)
CKernel * create_linearstring(int32_t size=10, float64_t scale=-1)
CKernel * create_localityimprovedstring(int32_t size=10, int32_t length=3, int32_t inner_degree=3, int32_t outer_degree=1, EKernelType ktype=K_LOCALITYIMPROVED)
CKernel * create_linearword(int32_t size=10, float64_t scale=-1)
CKernel * create_weighteddegreepositionstring2(int32_t size=10, int32_t order=3, int32_t max_mismatch=1, int32_t *shifts=NULL, int32_t length=0, bool use_normalization=true)
CKernel * create_gaussianshift(int32_t size=10, float64_t width=1, int32_t max_shift=0, int32_t shift_step=1)
bool init_kernel(const char *target)
CKernel * create_linearbyte(int32_t size=10, float64_t scale=-1)
CKernel * create_combined(int32_t size=10, bool append_subkernel_weights=false)
CKernel * create_custom(float64_t *kmatrix, int32_t num_feat, int32_t num_vec, bool source_is_diag, bool dest_is_diag)
bool save_kernel(char *filename)
CKernel * create_localalignmentstring(int32_t size=10)
CKernel * create_salzbergword(int32_t size=10)
bool set_optimization_type(char *opt_type)
CKernel * create_weighteddegreepositionstring3(int32_t size=10, int32_t order=3, int32_t max_mismatch=1, int32_t *shifts=NULL, int32_t length=0, int32_t mkl_stepsize=1, float64_t *position_weights=NULL)
CKernel * create_weighteddegreerbf(int32_t size=10, int32_t degree=1, int32_t nof_properties=1, float64_t width=1)
CKernel * create_const(int32_t size=10, float64_t c=1)
Class SGObject is the base class of all shogun objects.
CKernel * create_weighteddegreestring(int32_t size=10, int32_t order=3, int32_t max_mismatch=1, bool use_normalization=true, int32_t mkl_stepsize=1, bool block_computation=true, int32_t single_degree=-1)
CKernel * create_sigmoid(int32_t size=10, float64_t gamma=0.01, float64_t coef0=0)
CKernel * create_poly(int32_t size=10, int32_t degree=2, bool inhomogene=false, bool normalize=true)
CKernel * create_diag(int32_t size=10, float64_t diag=1)
CKernel * create_chi2(int32_t size=10, float64_t width=1)
bool delete_kernel_optimization()
all of classes and functions are contained in the shogun namespace
CKernel * create_matchwordstring(int32_t size=10, int32_t d=3, bool normalize=true)
void scale(Matrix A, Matrix B, typename Matrix::Scalar alpha)
CKernel * create_wavelet(int32_t size=10, float64_t Wdilation=5.0, float64_t Wtranslation=2.0)
bool precompute_subkernels()
CKernel * create_gaussian(int32_t size=10, float64_t width=1)
CKernel * create_oligo(int32_t size, int32_t k, float64_t width)
CKernel * create_tppk(int32_t size, float64_t *km, int32_t rows, int32_t cols)
bool init_kernel_optimization()
bool set_kernel(CKernel *kern)
CKernel * create_distance(int32_t size=10, float64_t width=1)
virtual const char * get_name() const
CKernel * create_polymatchstring(int32_t size=10, int32_t degree=2, bool inhomogene=false, bool normalize=true)
bool add_kernel(CKernel *kern, float64_t weight=1)
CKernel * create_sparsegaussian(int32_t size=10, float64_t width=1)
bool set_normalization(char *normalization, float64_t c=0.0, float64_t r=0.0)