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CPCA Class Reference

Detailed Description

Preprocessor PCA performs principial component analysis on input feature vectors/matrices. When the init method in PCA is called with proper feature matrix X (with say N number of vectors and D feature dimension), a transformation matrix is computed and stored internally. This transformation matrix is then used to transform all D-dimensional feature vectors or feature matrices (with D feature dimensions) supplied via apply_to_feature_matrix or apply_to_feature_vector methods. This tranformation outputs the T-Dimensional approximation of all these input vectors and matrices (where T<=min(D,N)). The transformation matrix is essentially a DxT matrix, the columns of which correspond to the eigenvectors of the covariance matrix(XX') having top T eigenvalues.

This class provides 3 method options to compute the transformation matrix : EVD : Eigen Value Decomposition of Covariance Matrix ( \(XX^T\)) The covariance matrix \(XX^T\) is first formed internally and then its eigenvectors and eigenvalues are computed using QR decomposition of the matrix. The time complexity of this method is \(~10D^3\) and should be used when N > D.

SVD : Singular Value Decomposition of feature matrix X The transpose of feature matrix, \(X^T\), is decomposed using SVD. \(X^T = UDV^T\) The matrix V in this decomposition contains the required eigenvectors and the diagonal entries of the diagonal matrix D correspond to the non-negative eigenvalues. Eigenvalue, \(e_i\), is derived from a diagonal element, \(d_i\), using the formula \(e_i = \frac{\sqrt{d_i}}{N-1}\). The time complexity of this method is \(~14DN^2\) and should be used when N < D.

AUTO : This mode automagically chooses one of the above modes for the user based on whether N > D (chooses EVD) or N < D (chooses SVD).

This class provides 3 modes to determine the value of T :

FIXED_NUMBER : T is supplied by user directly using set_target_dims method

VARIANCE_EXPLAINED : The user supplies the fractional variance that he wants preserved in the target dimension T. From this supplied fractional variance (thresh), T is calculated as the smallest k such that the ratio of sum of largest k eigenvalues over total sum of all eigenvalues is greater than thresh.

THRESH : The user supplies a threshold. All eigenvectors with corresponding eigenvalue greater than the supplied threshold are chosen.

An option for whitening the transformation matrix is also given - do_whitening. Setting this option normalizes the eigenvectors (ie. the columns of transformation matrix) by dividing them with the square root of corresponding eigenvalues.

Note that vectors/matrices don't have to have zero mean as it is substracted within the class.

Definition at line 113 of file PCA.h.

Inheritance diagram for CPCA:
Inheritance graph
[legend]

Public Member Functions

 CPCA (bool do_whitening=false, EPCAMode mode=FIXED_NUMBER, float64_t thresh=1e-6, EPCAMethod method=AUTO, EPCAMemoryMode mem_mode=MEM_REALLOCATE)
 CPCA (EPCAMethod method, bool do_whitening=false, EPCAMemoryMode mem=MEM_REALLOCATE)
virtual ~CPCA ()
virtual bool init (CFeatures *features)
virtual void cleanup ()
virtual SGMatrix< float64_tapply_to_feature_matrix (CFeatures *features)
virtual SGVector< float64_tapply_to_feature_vector (SGVector< float64_t > vector)
SGMatrix< float64_tget_transformation_matrix ()
SGVector< float64_tget_eigenvalues ()
SGVector< float64_tget_mean ()
virtual const char * get_name () const
virtual EPreprocessorType get_type () const
EPCAMemoryMode get_memory_mode () const
void set_memory_mode (EPCAMemoryMode e)
void set_eigenvalue_zero_tolerance (float64_t eigenvalue_zero_tolerance=1e-15)
float64_t get_eigenvalue_zero_tolerance () const
void set_target_dim (int32_t dim)
int32_t get_target_dim () const
void set_distance (CDistance *distance)
CDistanceget_distance () const
void set_kernel (CKernel *kernel)
CKernelget_kernel () const
virtual CFeaturesapply (CFeatures *features)
virtual EFeatureClass get_feature_class ()
 return that we are dense features (just fixed size matrices)
virtual EFeatureType get_feature_type ()
 return feature 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 void update_parameter_hash ()
virtual bool parameter_hash_changed ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
virtual CSGObjectclone ()

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

void init ()
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

SGMatrix< float64_tm_transformation_matrix
int32_t num_dim
int32_t num_old_dim
SGVector< float64_tm_mean_vector
SGVector< float64_tm_eigenvalues_vector
bool m_initialized
bool m_whitening
EPCAMode m_mode
float64_t m_thresh
EPCAMemoryMode m_mem_mode
EPCAMethod m_method
float64_t m_eigenvalue_zero_tolerance
int32_t m_target_dim
CDistancem_distance
CKernelm_kernel
CEmbeddingConverterm_converter

Constructor & Destructor Documentation

CPCA ( bool  do_whitening = false,
EPCAMode  mode = FIXED_NUMBER,
float64_t  thresh = 1e-6,
EPCAMethod  method = AUTO,
EPCAMemoryMode  mem_mode = MEM_REALLOCATE 
)

standard constructor

Parameters
do_whiteningnormalize columns(eigenvectors) in transformation matrix
modemode of pca : FIXED_NUMBER/VARIANCE_EXPLAINED/THRESHOLD
threshthreshold value for VARIANCE_EXPLAINED or THRESHOLD mode
methodMatrix decomposition method used : SVD/EVD/AUTO[default]
mem_modememory usage mode of PCA : MEM_REALLOCATE/MEM_IN_PLACE

Definition at line 26 of file PCA.cpp.

CPCA ( EPCAMethod  method,
bool  do_whitening = false,
EPCAMemoryMode  mem = MEM_REALLOCATE 
)

special constructor for FIXED_NUMBER mode

Parameters
methodMatrix decomposition method used : SVD/EVD/AUTO[default]
do_whiteningnormalize columns(eigenvectors) in transformation matrix
memmemory usage mode of PCA : MEM_REALLOCATE/MEM_IN_PLACE

Definition at line 37 of file PCA.cpp.

~CPCA ( )
virtual

destructor

Definition at line 80 of file PCA.cpp.

Member Function Documentation

virtual CFeatures* apply ( CFeatures features)
virtualinherited

generic interface for applying the preprocessor. used as a wrapper for apply_to_feature_matrix() method

Parameters
featuresthe dense input features
Returns
the result feature object after applying the preprocessor

Implements CPreprocessor.

SGMatrix< float64_t > apply_to_feature_matrix ( CFeatures features)
virtual

apply preprocessor to feature matrix

Parameters
featuresfeatures
Returns
processed feature matrix

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 278 of file PCA.cpp.

SGVector< float64_t > apply_to_feature_vector ( SGVector< float64_t vector)
virtual

apply preprocessor to feature vector

Parameters
vectorfeature vector
Returns
processed feature vector

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 333 of file PCA.cpp.

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
dictdictionary of parameters to be built.

Definition at line 1189 of file SGObject.cpp.

void cleanup ( )
virtual

cleanup

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 270 of file PCA.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 1306 of file SGObject.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 146 of file SGObject.cpp.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 
)
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
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 1210 of file SGObject.cpp.

CDistance * get_distance ( ) const
inherited

getter for distance

Returns
distance

Definition at line 88 of file DimensionReductionPreprocessor.cpp.

float64_t get_eigenvalue_zero_tolerance ( ) const

get zero tolerance of eigenvalues during data whitening

Returns
zero tolerance value

Definition at line 380 of file PCA.cpp.

SGVector< float64_t > get_eigenvalues ( )

get eigenvalues of PCA

Definition at line 355 of file PCA.cpp.

virtual EFeatureClass get_feature_class ( )
virtualinherited

return that we are dense features (just fixed size matrices)

Implements CPreprocessor.

Reimplemented in CRandomFourierGaussPreproc.

virtual EFeatureType get_feature_type ( )
virtualinherited

return feature type

Implements CPreprocessor.

Reimplemented in CRandomFourierGaussPreproc.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 183 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 224 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 237 of file SGObject.cpp.

CKernel * get_kernel ( ) const
inherited

getter for kernel

Returns
kernel

Definition at line 101 of file DimensionReductionPreprocessor.cpp.

SGVector< float64_t > get_mean ( )

get mean vector of original data

Definition at line 360 of file PCA.cpp.

EPCAMemoryMode get_memory_mode ( ) const

return the PCA memory mode being used

Definition at line 365 of file PCA.cpp.

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

Definition at line 1081 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_namename of the parameter
Returns
description of the parameter

Definition at line 1105 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_namename of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1118 of file SGObject.cpp.

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

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 173 of file PCA.h.

int32_t get_target_dim ( ) const
inherited

getter for target dimension

Returns
target dimension

Definition at line 76 of file DimensionReductionPreprocessor.cpp.

SGMatrix< float64_t > get_transformation_matrix ( )

get transformation matrix, i.e. eigenvectors (potentially scaled if do_whitening is true)

Definition at line 350 of file PCA.cpp.

virtual EPreprocessorType get_type ( ) const
virtual
Returns
a type of preprocessor

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 176 of file PCA.h.

bool init ( CFeatures features)
virtual

initialize preprocessor from features

Parameters
features

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 84 of file PCA.cpp.

void init ( )
protected

default init

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 46 of file PCA.cpp.

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

Definition at line 243 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_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
Returns
(sorted) array of created TParameter instances with file data

Definition at line 650 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_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
Returns
new array with TParameter instances with the attached data

Definition at line 491 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
filewhere to load from
prefixprefix 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 320 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
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 1008 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
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 1003 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_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

Definition at line 688 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_baseset of TParameter instances to use for migration
targetparameter 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 895 of file SGObject.cpp.

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_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

Definition at line 835 of file SGObject.cpp.

bool parameter_hash_changed ( )
virtualinherited
Returns
whether parameter combination has changed since last update

Definition at line 209 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1057 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 255 of file SGObject.cpp.

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

Save this object to file.

Parameters
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix 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 261 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
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 1018 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
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 1013 of file SGObject.cpp.

void set_distance ( CDistance distance)
inherited

setter for distance

Parameters
distancedistance to set

Definition at line 81 of file DimensionReductionPreprocessor.cpp.

void set_eigenvalue_zero_tolerance ( float64_t  eigenvalue_zero_tolerance = 1e-15)

set zero tolerance of eigenvalues during data whitening

Parameters
eigenvalue_zero_tolerancezero tolerance value

Definition at line 375 of file PCA.cpp.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 38 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 176 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 189 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 230 of file SGObject.cpp.

void set_kernel ( CKernel kernel)
inherited

setter for kernel

Parameters
kernelkernel to set

Definition at line 94 of file DimensionReductionPreprocessor.cpp.

void set_memory_mode ( EPCAMemoryMode  e)

set PCA memory mode to be used

Parameters
choicebetween MEM_REALLOCATE and MEM_IN_PLACE

Definition at line 370 of file PCA.cpp.

void set_target_dim ( int32_t  dim)
inherited

setter for target dimension

Parameters
dimtarget dimension

Definition at line 70 of file DimensionReductionPreprocessor.cpp.

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 140 of file SGObject.cpp.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 250 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 196 of file SGObject.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 457 of file SGObject.h.

CEmbeddingConverter* m_converter
protectedinherited

embedding converter to be used

Definition at line 127 of file DimensionReductionPreprocessor.h.

CDistance* m_distance
protectedinherited

distance to be used

Definition at line 121 of file DimensionReductionPreprocessor.h.

float64_t m_eigenvalue_zero_tolerance
protected

eigenvalues within zero tolerance region are considered 0 while whitening to tackle numerical issues

Definition at line 228 of file PCA.h.

SGVector<float64_t> m_eigenvalues_vector
protected

eigenvalues vector

Definition at line 211 of file PCA.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 472 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 478 of file SGObject.h.

bool m_initialized
protected

initialized

Definition at line 213 of file PCA.h.

CKernel* m_kernel
protectedinherited

kernel to be used

Definition at line 124 of file DimensionReductionPreprocessor.h.

SGVector<float64_t> m_mean_vector
protected

mean vector

Definition at line 209 of file PCA.h.

EPCAMemoryMode m_mem_mode
protected

PCA memory mode

Definition at line 221 of file PCA.h.

EPCAMethod m_method
protected

PCA method

Definition at line 223 of file PCA.h.

EPCAMode m_mode
protected

PCA mode

Definition at line 217 of file PCA.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 469 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 475 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 466 of file SGObject.h.

int32_t m_target_dim
protectedinherited

target dim of dimensionality reduction preprocessor

Definition at line 118 of file DimensionReductionPreprocessor.h.

float64_t m_thresh
protected

thresh

Definition at line 219 of file PCA.h.

SGMatrix<float64_t> m_transformation_matrix
protected

transformation matrix

Definition at line 203 of file PCA.h.

bool m_whitening
protected

whitening

Definition at line 215 of file PCA.h.

int32_t num_dim
protected

num dim

Definition at line 205 of file PCA.h.

int32_t num_old_dim
protected

num old dim

Definition at line 207 of file PCA.h.

Parallel* parallel
inherited

parallel

Definition at line 460 of file SGObject.h.

Version* version
inherited

version

Definition at line 463 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation