CPolyMatchStringKernel Class Reference


Detailed Description

The class PolyMatchStringKernel computes a variant of the polynomial kernel on strings of same length.

It is computed as

\[ k({\bf x},{\bf x'})= (\sum_{i=0}^L I(x_i=x'_i)+c)^d \]

where I is the indicator function which evaluates to 1 if its argument is true and to 0 otherwise.

Note that additional normalisation is applied, i.e.

\[ k'({\bf x}, {\bf x'})=\frac{k({\bf x}, {\bf x'})}{\sqrt{k({\bf x}, {\bf x})k({\bf x'}, {\bf x'})}} \]

Definition at line 34 of file PolyMatchStringKernel.h.

Inheritance diagram for CPolyMatchStringKernel:
Inheritance graph
[legend]

List of all members.

Public Member Functions

 CPolyMatchStringKernel (int32_t size, int32_t degree, bool inhomogene)
 CPolyMatchStringKernel (CStringFeatures< char > *l, CStringFeatures< char > *r, int32_t degree, bool inhomogene)
virtual ~CPolyMatchStringKernel ()
virtual bool init (CFeatures *l, CFeatures *r)
virtual void cleanup ()
virtual bool load_init (FILE *src)
virtual bool save_init (FILE *dest)
virtual EKernelType get_kernel_type ()
virtual const char * get_name () const

Protected Member Functions

virtual float64_t compute (int32_t idx_a, int32_t idx_b)

Protected Attributes

int32_t degree
bool inhomogene

Constructor & Destructor Documentation

CPolyMatchStringKernel::CPolyMatchStringKernel ( int32_t  size,
int32_t  degree,
bool  inhomogene 
)

constructor

Parameters:
size cache size
degree degree
inhomogene is inhomogeneous

Definition at line 18 of file PolyMatchStringKernel.cpp.

CPolyMatchStringKernel::CPolyMatchStringKernel ( CStringFeatures< char > *  l,
CStringFeatures< char > *  r,
int32_t  degree,
bool  inhomogene 
)

constructor

Parameters:
l features of left-hand side
r features of right-hand side
degree degree
inhomogene is inhomogeneous

Definition at line 24 of file PolyMatchStringKernel.cpp.

CPolyMatchStringKernel::~CPolyMatchStringKernel (  )  [virtual]

Definition at line 32 of file PolyMatchStringKernel.cpp.


Member Function Documentation

void CPolyMatchStringKernel::cleanup (  )  [virtual]

clean up kernel

Reimplemented from CKernel.

Definition at line 43 of file PolyMatchStringKernel.cpp.

float64_t CPolyMatchStringKernel::compute ( int32_t  idx_a,
int32_t  idx_b 
) [protected, virtual]

compute kernel function for features a and b idx_{a,b} denote the index of the feature vectors in the corresponding feature object

Parameters:
idx_a index a
idx_b index b
Returns:
computed kernel function at indices a,b

Implements CKernel.

Definition at line 58 of file PolyMatchStringKernel.cpp.

virtual EKernelType CPolyMatchStringKernel::get_kernel_type (  )  [virtual]

return what type of kernel we are

Returns:
kernel type POLYMATCH

Implements CKernel.

Definition at line 87 of file PolyMatchStringKernel.h.

virtual const char* CPolyMatchStringKernel::get_name (  )  const [virtual]

return the kernel's name

Returns:
name PolyMatchString

Implements CSGObject.

Definition at line 96 of file PolyMatchStringKernel.h.

bool CPolyMatchStringKernel::init ( CFeatures l,
CFeatures r 
) [virtual]

initialize kernel

Parameters:
l features of left-hand side
r features of right-hand side
Returns:
if initializing was successful

Reimplemented from CStringKernel< char >.

Definition at line 37 of file PolyMatchStringKernel.cpp.

bool CPolyMatchStringKernel::load_init ( FILE *  src  )  [virtual]

load kernel init_data

Parameters:
src file to load from
Returns:
if loading was successful

Implements CKernel.

Definition at line 48 of file PolyMatchStringKernel.cpp.

bool CPolyMatchStringKernel::save_init ( FILE *  dest  )  [virtual]

save kernel init_data

Parameters:
dest file to save to
Returns:
if saving was successful

Implements CKernel.

Definition at line 53 of file PolyMatchStringKernel.cpp.


Member Data Documentation

int32_t CPolyMatchStringKernel::degree [protected]

degree

Definition at line 111 of file PolyMatchStringKernel.h.

if kernel is inhomogeneous

Definition at line 113 of file PolyMatchStringKernel.h.


The documentation for this class was generated from the following files:

SHOGUN Machine Learning Toolbox - Documentation