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CFisherLDA Class Reference

Detailed Description

Preprocessor FisherLDA attempts to model the difference between the classes of data by performing linear discriminant analysis on input feature vectors/matrices. When the init method in FisherLDA is called with proper feature matrix X(say N number of vectors and D feature dimensions) supplied via apply_to_feature_matrix or apply_to_feature_vector methods, this creates a transformation whose outputs are the reduced T-Dimensional & class-specific distribution (where T<= number of unique classes-1). The transformation matrix is essentially a DxT matrix, the columns of which correspond to the specified number of eigenvectors which maximizes the ratio of between class matrix to within class matrix.

This class provides 3 method options to compute the transformation matrix :

CLASSIC_FLDA : This method selects W in such a way that the ratio of the between-class scatter and the within class scatter is maximized. The between class matrix is : \(\sum_b = \sum_{i=1}^C{\bf{(\mu_i-\mu)(\mu_i-\mu)^T}}\) The within class matrix is : \(\sum_w = \sum_{i=1}^C{\sum_{x_k\in}^c{\bf{(\mu_i-\mu)(\mu_i-\mu)^T}}}\) This should be choosen when N>D

CANVAR_FLDA : This method performs Canonical Variates which generalises Fisher's method to projection of more than one dimension. This is equipped to handle the cases where the within class matrix are non-invertible. Can be used for both cases(D>N or D<N). See the implementation in Bayesian Reasoning and Machine Learning by David Barber , Section 16.3

AUTO_FLDA : Automagically, the appropriate method is selected based on whether D>N (chooses CANVAR_FLDA) or D<N(chooses ::CLASSIC_FLDA)

Definition at line 93 of file FisherLDA.h.

Inheritance diagram for CFisherLDA:
Inheritance graph
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Public Member Functions

 CFisherLDA (EFLDAMethod method=AUTO_FLDA, float64_t thresh=0.01)
virtual ~CFisherLDA ()
virtual bool init (CFeatures *features, CLabels *labels, int32_t num_dimensions=0)
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
virtual bool init (CFeatures *data)
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 m_num_dim
float64_t m_threshold
int32_t m_method
SGVector< float64_tm_mean_vector
SGVector< float64_tm_eigenvalues_vector
int32_t m_target_dim
CDistancem_distance
CKernelm_kernel
CEmbeddingConverterm_converter

Constructor & Destructor Documentation

CFisherLDA ( EFLDAMethod  method = AUTO_FLDA,
float64_t  thresh = 0.01 
)

standard constructor

Parameters
methodLDA based on : CLASSIC_FLDA/CANVAR_FLDA/AUTO_FLDA[default]
threshthreshold value for CANVAR_FLDA only. This is used to reject those basis whose singular values are less than the provided threshold. The default one is 0.01.

Definition at line 51 of file FisherLDA.cpp.

~CFisherLDA ( )
virtual

destructor

Definition at line 75 of file FisherLDA.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
featureson which the learned tranformation has to be applied. Sometimes it is also referred as projecting the given features.
Returns
processed feature matrix with reduced dimensions.

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 293 of file FisherLDA.cpp.

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

apply preprocessor to feature vector

Parameters
featureson which the learned transformation has to be applied.
Returns
processed feature vector with reduced dimensions.

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 330 of file FisherLDA.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 1185 of file SGObject.cpp.

void cleanup ( )
virtual

cleanup

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 286 of file FisherLDA.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 1302 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 1206 of file SGObject.cpp.

CDistance * get_distance ( ) const
inherited

getter for distance

Returns
distance

Definition at line 88 of file DimensionReductionPreprocessor.cpp.

SGVector< float64_t > get_eigenvalues ( )
Returns
get eigenvalues of LDA

Definition at line 349 of file FisherLDA.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 ( )
Returns
get mean vector of the original data

Definition at line 354 of file FisherLDA.cpp.

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

Definition at line 1077 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 1101 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 1114 of file SGObject.cpp.

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

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 145 of file FisherLDA.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 ( )
Returns
get transformation matrix which contains the required number of eigenvectors

Definition at line 344 of file FisherLDA.cpp.

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

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 148 of file FisherLDA.h.

bool init ( CFeatures data)
virtualinherited

init set true by default, should be defined if dimension reduction preprocessor is using some initialization

Implements CPreprocessor.

Reimplemented in CPCA, and CKernelPCA.

Definition at line 58 of file DimensionReductionPreprocessor.cpp.

bool init ( CFeatures features,
CLabels labels,
int32_t  num_dimensions = 0 
)
virtual

initialize preprocessor from features and corresponding labels

Parameters
featuresusing which the transformation matrix will be formed
labelsof the given features which will be used here to find the transformation matrix unlike PCA where it is not needed.
dimensionsnumber of dimensions to retain

Definition at line 79 of file FisherLDA.cpp.

void init ( )
protected

default init

Reimplemented from CDimensionReductionPreprocessor.

Definition at line 59 of file FisherLDA.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 648 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 489 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 occurres.

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

Definition at line 1004 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 occurres.

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

Definition at line 999 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 686 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 893 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 833 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 1053 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 occurres.

Reimplemented in CKernel.

Definition at line 1014 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 occurres.

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

Definition at line 1009 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_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_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 461 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.

SGVector<float64_t> m_eigenvalues_vector
protected

eigenvalues vector

Definition at line 165 of file FisherLDA.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 476 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 482 of file SGObject.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 163 of file FisherLDA.h.

int32_t m_method
protected

m_method

Definition at line 161 of file FisherLDA.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 473 of file SGObject.h.

int32_t m_num_dim
protected

num dim

Definition at line 157 of file FisherLDA.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 479 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 470 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_threshold
protected

m_threshold

Definition at line 159 of file FisherLDA.h.

SGMatrix<float64_t> m_transformation_matrix
protected

transformation matrix

Definition at line 155 of file FisherLDA.h.

Parallel* parallel
inherited

parallel

Definition at line 464 of file SGObject.h.

Version* version
inherited

version

Definition at line 467 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation