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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. 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 112 of file PCA.h.

Inheritance diagram for CPCA:
[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_t > apply_to_feature_matrix (CFeatures *features)
 
virtual SGVector< float64_t > apply_to_feature_vector (SGVector< float64_t > vector)
 
SGMatrix< float64_t > get_transformation_matrix ()
 
SGVector< float64_t > get_eigenvalues ()
 
SGVector< float64_t > get_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)
 
CDistance * get_distance () const
 
void set_kernel (CKernel *kernel)
 
CKernel * get_kernel () const
 
virtual CFeatures * apply (CFeatures *features)
 
virtual EFeatureClass get_feature_class ()
 return that we are dense features (just fixed size matrices) More...
 
virtual EFeatureType get_feature_type ()
 return feature type More...
 
virtual CSGObject * shallow_copy () const
 
virtual CSGObject * deep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
 
void set_global_io (SGIO *io)
 
SGIO * get_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallel * get_global_parallel ()
 
void set_global_version (Version *version)
 
Version * get_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)
 
bool has (const std::string &name) const
 
template<typename T >
bool has (const Tag< T > &tag) const
 
template<typename T , typename U = void>
bool has (const std::string &name) const
 
template<typename T >
void set (const Tag< T > &_tag, const T &value)
 
template<typename T , typename U = void>
void set (const std::string &name, const T &value)
 
template<typename T >
T get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
T get (const std::string &name) const
 
virtual void update_parameter_hash ()
 
virtual bool parameter_hash_changed ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
 
virtual CSGObject * clone ()
 

Public Attributes

SGIO * io
 
Parallel * parallel
 
Version * version
 
Parameter * m_parameters
 
Parameter * m_model_selection_parameters
 
Parameter * m_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

void init ()
 
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)
 
template<typename T >
void register_param (Tag< T > &_tag, const T &value)
 
template<typename T >
void register_param (const std::string &name, const T &value)
 

Protected Attributes

SGMatrix< float64_t > m_transformation_matrix
 
int32_t num_dim
 
int32_t num_old_dim
 
SGVector< float64_t > m_mean_vector
 
SGVector< float64_t > m_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
 
CDistance * m_distance
 
CKernel * m_kernel
 
CEmbeddingConverter * m_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 25 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 36 of file PCA.cpp.

~CPCA ( )
virtual

destructor

Definition at line 79 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 277 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 332 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 630 of file SGObject.cpp.

void cleanup ( )
virtual

cleanup

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 269 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 747 of file SGObject.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 231 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 651 of file SGObject.cpp.

T get ( const Tag< T > &  _tag) const
inherited

Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
Returns
value of the parameter identified by the input tag

Definition at line 367 of file SGObject.h.

T get ( const std::string &  name) const
inherited

Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
Returns
value of the parameter corresponding to the input name and type

Definition at line 388 of file SGObject.h.

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 379 of file PCA.cpp.

SGVector< float64_t > get_eigenvalues ( )

get eigenvalues of PCA

Definition at line 354 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 268 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 310 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 323 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 359 of file PCA.cpp.

EPCAMemoryMode get_memory_mode ( ) const

return the PCA memory mode being used

Definition at line 364 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 531 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 555 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 568 of file SGObject.cpp.

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

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 172 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 349 of file PCA.cpp.

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

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 175 of file PCA.h.

bool has ( const std::string &  name) const
inherited

Checks if object has a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name

Definition at line 289 of file SGObject.h.

bool has ( const Tag< T > &  tag) const
inherited

Checks if object has a class parameter identified by a Tag.

Parameters
tagtag of the parameter containing name and type information
Returns
true if the parameter exists with the input tag

Definition at line 301 of file SGObject.h.

bool has ( const std::string &  name) const
inherited

Checks if a type exists for a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name and type

Definition at line 312 of file SGObject.h.

bool init ( CFeatures *  features)
virtual

initialize preprocessor from features

Parameters
features

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 83 of file PCA.cpp.

void init ( )
protected

Definition at line 45 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 329 of file SGObject.cpp.

bool load_serializable ( CSerializableFile *  file,
const char *  prefix = "" 
)
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
Returns
TRUE if done, otherwise FALSE

Definition at line 402 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 459 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 454 of file SGObject.cpp.

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

Definition at line 295 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 507 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 341 of file SGObject.cpp.

void register_param ( Tag< T > &  _tag,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 439 of file SGObject.h.

void register_param ( const std::string &  name,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 452 of file SGObject.h.

bool save_serializable ( CSerializableFile *  file,
const char *  prefix = "" 
)
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
Returns
TRUE if done, otherwise FALSE

Definition at line 347 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 469 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 464 of file SGObject.cpp.

void set ( const Tag< T > &  _tag,
const T &  value 
)
inherited

Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 328 of file SGObject.h.

void set ( const std::string &  name,
const T &  value 
)
inherited

Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 354 of file SGObject.h.

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 374 of file PCA.cpp.

void set_generic ( )
inherited

Definition at line 74 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 79 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 84 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 89 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 94 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 99 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 104 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 109 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 114 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 119 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 124 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 129 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 134 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 139 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 144 of file SGObject.cpp.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO *  io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 261 of file SGObject.cpp.

void set_global_parallel ( Parallel *  parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 274 of file SGObject.cpp.

void set_global_version ( Version *  version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 316 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
ehoice between MEM_REALLOCATE and MEM_IN_PLACE

Definition at line 369 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 225 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 336 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 281 of file SGObject.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 537 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 227 of file PCA.h.

SGVector<float64_t> m_eigenvalues_vector
protected

eigenvalues vector

Definition at line 210 of file PCA.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 552 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 555 of file SGObject.h.

bool m_initialized
protected

initialized

Definition at line 212 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 208 of file PCA.h.

EPCAMemoryMode m_mem_mode
protected

PCA memory mode

Definition at line 220 of file PCA.h.

EPCAMethod m_method
protected

PCA method

Definition at line 222 of file PCA.h.

EPCAMode m_mode
protected

PCA mode

Definition at line 216 of file PCA.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 549 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 546 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 218 of file PCA.h.

SGMatrix<float64_t> m_transformation_matrix
protected

transformation matrix

Definition at line 202 of file PCA.h.

bool m_whitening
protected

whitening

Definition at line 214 of file PCA.h.

int32_t num_dim
protected

num dim

Definition at line 204 of file PCA.h.

int32_t num_old_dim
protected

num old dim

Definition at line 206 of file PCA.h.

Parallel* parallel
inherited

parallel

Definition at line 540 of file SGObject.h.

Version* version
inherited

version

Definition at line 543 of file SGObject.h.

The documentation for this class was generated from the following files:
SHOGUN Machine Learning Toolbox - Documentation