SHOGUN  v3.0.0
CZeroMeanCenterKernelNormalizer Class Reference

## Detailed Description

ZeroMeanCenterKernelNormalizer centers the kernel in feature space.

After centering, each feature must have zero mean. The centered kernel matrix can be expressed in terms of the non-centered version.

Denoting the mapping from input space to feature space by $$\phi:\mathcal{X}\rightarrow\mathcal{F}$$, the centered square kernel matrix $$K_c$$ (with dimensionality $$M$$)

can be expressed in terms of the original matrix $$K$$ as follows:

\begin{eqnarray*} k({\bf x}_i,{\bf x}_j)_c & = & \left(\phi({\bf x}_i) - \frac{1}{m} \sum_{p=1}^M \phi({\bf x}_p)\right) \cdot \left(\phi({\bf x}_j) - \frac{1}{M} \sum_{q=1}^M \phi({\bf x}_q)\right) \\ & = & K_{ij} - \frac{1}{M} \sum_{p=1}^M K_{pj} - \frac{1}{M} \sum_{q=1}^M K_{iq} + \frac{1}{M^2} \sum_{p=1}^M \sum_{q=1}^M K_{pq} \\ & = & (K - 1_M K - K 1_M + 1_M K 1_M)_{ij} \end{eqnarray*}

Additionally, let $$K^{t}$$ be the $$L \times M$$ test matrix describing the similarity between a $$L$$ test instances with $$M$$ training instances

(defined by a $$M x M$$ kernel matrix $$K$$), the centered testing set kernel matrix is given by

$K_{c}^t = (K - 1'_M K - K^{t} 1_M + 1'_M K 1_M)$

Definition at line 41 of file ZeroMeanCenterKernelNormalizer.h.

Inheritance diagram for CZeroMeanCenterKernelNormalizer:
[legend]

## Public Member Functions

CZeroMeanCenterKernelNormalizer ()
virtual ~CZeroMeanCenterKernelNormalizer ()
virtual bool init (CKernel *k)
virtual float64_t normalize (float64_t value, int32_t idx_lhs, int32_t idx_rhs)
virtual float64_t normalize_lhs (float64_t value, int32_t idx_lhs)
virtual float64_t normalize_rhs (float64_t value, int32_t idx_rhs)
bool alloc_and_compute_row_means (CKernel *k, float64_t *&v, int32_t num_lhs, int32_t num_rhs)
virtual const char * get_name () const
virtual void register_params ()
ENormalizerType get_normalizer_type ()
void set_normalizer_type (ENormalizerType type)
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_copy () const
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_global_version ()
SGStringList< char > get_modelsel_names ()
void print_modsel_params ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
virtual bool update_parameter_hash ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0)
virtual CSGObjectclone ()

## Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
ParameterMapm_parameter_map
uint32_t m_hash

## Protected Member Functions

virtual TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)
virtual void one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL)
virtual void load_serializable_pre () throw (ShogunException)
virtual void load_serializable_post () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)

## Protected Attributes

float64_tktrain_row_means
int32_t num_ktrain
float64_tktest_row_means
int32_t num_ktest
float64_t ktrain_mean
ENormalizerType m_type

## Constructor & Destructor Documentation

 CZeroMeanCenterKernelNormalizer ( )

default constructor

Definition at line 46 of file ZeroMeanCenterKernelNormalizer.h.

 virtual ~CZeroMeanCenterKernelNormalizer ( )
virtual

default destructor

Definition at line 57 of file ZeroMeanCenterKernelNormalizer.h.

## Member Function Documentation

 bool alloc_and_compute_row_means ( CKernel * k, float64_t *& v, int32_t num_lhs, int32_t num_rhs )

alloc and compute the vector containing the row margins of all rows for a kernel matrix.

Definition at line 135 of file ZeroMeanCenterKernelNormalizer.h.

 void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject * > * dict )
inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters
 dict dictionary of parameters to be built.

Definition at line 1196 of file SGObject.cpp.

 CSGObject * clone ( )
virtualinherited

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

Returns
an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

Definition at line 1313 of file SGObject.cpp.

 virtual CSGObject* deep_copy ( ) const
virtualinherited

A deep copy. All the instance variables will also be copied.

Definition at line 160 of file SGObject.h.

 bool equals ( CSGObject * other, float64_t accuracy = 0.0 )
virtualinherited

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

Parameters
 other object to compare with accuracy accuracy to use for comparison (optional)
Returns
true if all parameters were equal, false if not

Definition at line 1217 of file SGObject.cpp.

 SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 214 of file SGObject.cpp.

 Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 249 of file SGObject.cpp.

 Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 262 of file SGObject.cpp.

 SGStringList< char > get_modelsel_names ( )
inherited
Returns
vector of names of all parameters which are registered for model selection

Definition at line 1100 of file SGObject.cpp.

 char * get_modsel_param_descr ( const char * param_name )
inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

Parameters
 param_name name of the parameter
Returns
description of the parameter

Definition at line 1124 of file SGObject.cpp.

 index_t get_modsel_param_index ( const char * param_name )
inherited

Returns index of model selection parameter with provided index

Parameters
 param_name name of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1137 of file SGObject.cpp.

 virtual const char* get_name ( ) const
virtual
Returns
object name

Implements CSGObject.

Definition at line 150 of file ZeroMeanCenterKernelNormalizer.h.

 ENormalizerType get_normalizer_type ( )
inherited

getter for normalizer type

Definition at line 100 of file KernelNormalizer.h.

 virtual bool init ( CKernel * k )
virtual

initialization of the normalizer

Parameters
 k kernel

Implements CKernelNormalizer.

Definition at line 65 of file ZeroMeanCenterKernelNormalizer.h.

 bool is_generic ( EPrimitiveType * generic ) const
virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

Parameters
 generic set to the type of the generic if returning TRUE
Returns
TRUE if a class template.

Definition at line 268 of file SGObject.cpp.

 DynArray< TParameter * > * load_all_file_parameters ( int32_t file_version, int32_t current_version, CSerializableFile * file, const char * prefix = "" )
inherited

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

Parameters
 file_version parameter version of the file current_version version from which mapping begins (you want to use Version::get_version_parameter() for this in most cases) file file to load from prefix prefix for members
Returns
(sorted) array of created TParameter instances with file data

Definition at line 673 of file SGObject.cpp.

 DynArray< TParameter * > * load_file_parameters ( const SGParamInfo * param_info, int32_t file_version, CSerializableFile * file, const char * prefix = "" )
inherited

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

Parameters
 param_info information of parameter file_version parameter version of the file, must be <= provided parameter version file file to load from prefix prefix for members
Returns
new array with TParameter instances with the attached data

Definition at line 514 of file SGObject.cpp.

 bool load_serializable ( CSerializableFile * file, const char * prefix = "", int32_t param_version = Version::get_version_parameter() )
virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

Parameters
 file where to load from prefix prefix for members param_version (optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 345 of file SGObject.cpp.

 void load_serializable_post ( ) throw (ShogunException)
protectedvirtualinherited

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.

Exceptions
 ShogunException Will be thrown if an error occurres.

Definition at line 1029 of file SGObject.cpp.

 void load_serializable_pre ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

Exceptions
 ShogunException Will be thrown if an error occurres.

Definition at line 1024 of file SGObject.cpp.

 void map_parameters ( DynArray< TParameter * > * param_base, int32_t & base_version, DynArray< const SGParamInfo * > * target_param_infos )
inherited

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

Parameters
 param_base set of TParameter instances that are mapped to the provided target parameter infos base_version version of the parameter base target_param_infos set of SGParamInfo instances that specify the target parameter base

Definition at line 711 of file SGObject.cpp.

 TParameter * migrate ( DynArray< TParameter * > * param_base, const SGParamInfo * target )
protectedvirtualinherited

creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.

If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass

Parameters
 param_base set of TParameter instances to use for migration target parameter info for the resulting TParameter
Returns
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

Definition at line 918 of file SGObject.cpp.

 virtual float64_t normalize ( float64_t value, int32_t idx_lhs, int32_t idx_rhs )
virtual

normalize the kernel value

Parameters
 value kernel value idx_lhs index of left hand side vector idx_rhs index of right hand side vector

Implements CKernelNormalizer.

Definition at line 104 of file ZeroMeanCenterKernelNormalizer.h.

 virtual float64_t normalize_lhs ( float64_t value, int32_t idx_lhs )
virtual

normalize only the left hand side vector

Parameters
 value value of a component of the left hand side feature vector idx_lhs index of left hand side vector

Implements CKernelNormalizer.

Definition at line 115 of file ZeroMeanCenterKernelNormalizer.h.

 virtual float64_t normalize_rhs ( float64_t value, int32_t idx_rhs )
virtual

normalize only the right hand side vector

Parameters
 value value of a component of the right hand side feature vector idx_rhs index of right hand side vector

Implements CKernelNormalizer.

Definition at line 125 of file ZeroMeanCenterKernelNormalizer.h.

 void one_to_one_migration_prepare ( DynArray< TParameter * > * param_base, const SGParamInfo * target, TParameter *& replacement, TParameter *& to_migrate, char * old_name = NULL )
protectedvirtualinherited

This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)

Parameters
 param_base set of TParameter instances to use for migration target parameter info for the resulting TParameter replacement (used as output) here the TParameter instance which is returned by migration is created into to_migrate the only source that is used for migration old_name with this parameter, a name change may be specified

Definition at line 858 of file SGObject.cpp.

 void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1076 of file SGObject.cpp.

 void print_serializable ( const char * prefix = "" )
virtualinherited

prints registered parameters out

Parameters
 prefix prefix for members

Definition at line 280 of file SGObject.cpp.

 virtual void register_params ( )
virtualinherited

register the parameters

Definition at line 92 of file KernelNormalizer.h.

 bool save_serializable ( CSerializableFile * file, const char * prefix = "", int32_t param_version = Version::get_version_parameter() )
virtualinherited

Save this object to file.

Parameters
 file where to save the object; will be closed during returning if PREFIX is an empty string. prefix prefix for members param_version (optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 286 of file SGObject.cpp.

 void save_serializable_post ( ) throw (ShogunException)
protectedvirtualinherited

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::SAVE_SERIALIZABLE_POST is called.

Exceptions
 ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1039 of file SGObject.cpp.

 void save_serializable_pre ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

Exceptions
 ShogunException Will be thrown if an error occurres.

Definition at line 1034 of file SGObject.cpp.

 void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 41 of file SGObject.cpp.

 void set_global_io ( SGIO * io )
inherited

set the io object

Parameters
 io io object to use

Definition at line 207 of file SGObject.cpp.

 void set_global_parallel ( Parallel * parallel )
inherited

set the parallel object

Parameters
 parallel parallel object to use

Definition at line 220 of file SGObject.cpp.

 void set_global_version ( Version * version )
inherited

set the version object

Parameters
 version version object to use

Definition at line 255 of file SGObject.cpp.

 void set_normalizer_type ( ENormalizerType type )
inherited

setter for normalizer type

Parameters
 type type of normalizer

Definition at line 108 of file KernelNormalizer.h.

 virtual CSGObject* shallow_copy ( ) const
virtualinherited

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

Reimplemented in CGaussianKernel.

Definition at line 151 of file SGObject.h.

 void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 275 of file SGObject.cpp.

 bool update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination.

Returns
bool if parameter combination has changed since last update.

Definition at line 227 of file SGObject.cpp.

## Member Data Documentation

 SGIO* io
inherited

io

Definition at line 514 of file SGObject.h.

 float64_t* ktest_row_means
protected

test row means

Definition at line 160 of file ZeroMeanCenterKernelNormalizer.h.

 float64_t ktrain_mean
protected

train mean

Definition at line 166 of file ZeroMeanCenterKernelNormalizer.h.

 float64_t* ktrain_row_means
protected

train row means

Definition at line 154 of file ZeroMeanCenterKernelNormalizer.h.

inherited

parameters wrt which we can compute gradients

Definition at line 529 of file SGObject.h.

 uint32_t m_hash
inherited

Hash of parameter values

Definition at line 535 of file SGObject.h.

 Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 526 of file SGObject.h.

 ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 532 of file SGObject.h.

 Parameter* m_parameters
inherited

parameters

Definition at line 523 of file SGObject.h.

 ENormalizerType m_type
protectedinherited

normalizer type

Definition at line 115 of file KernelNormalizer.h.

 int32_t num_ktest
protected

num k test

Definition at line 163 of file ZeroMeanCenterKernelNormalizer.h.

 int32_t num_ktrain
protected

num k train

Definition at line 157 of file ZeroMeanCenterKernelNormalizer.h.

 Parallel* parallel
inherited

parallel

Definition at line 517 of file SGObject.h.

 Version* version
inherited

version

Definition at line 520 of file SGObject.h.

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

SHOGUN Machine Learning Toolbox - Documentation