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CLinearTimeMMD Class Reference

Detailed Description

Definition at line 40 of file LinearTimeMMD.h.

Inheritance diagram for CLinearTimeMMD:
[legend]

Public Types

typedef std::function
< float32_t(SGMatrix
< float32_t >)> 
operation
 

Public Member Functions

 CLinearTimeMMD ()
 
 CLinearTimeMMD (CFeatures *samples_from_p, CFeatures *samples_from_q)
 
virtual ~CLinearTimeMMD ()
 
void set_num_blocks_per_burst (index_t num_blocks_per_burst)
 
virtual float64_t compute_p_value (float64_t statistic)
 
virtual float64_t compute_threshold (float64_t alpha)
 
virtual const char * get_name () const
 
virtual float64_t compute_statistic ()
 
virtual float64_t compute_variance ()
 
virtual SGVector< float64_tcompute_multiple ()
 
virtual SGVector< float64_tsample_null ()
 
void use_gpu (bool gpu)
 
void cleanup ()
 
void set_statistic_type (EStatisticType stype)
 
const EStatisticType get_statistic_type () const
 
void set_variance_estimation_method (EVarianceEstimationMethod vmethod)
 
const EVarianceEstimationMethod get_variance_estimation_method () const
 
void set_num_null_samples (index_t null_samples)
 
const index_t get_num_null_samples () const
 
void set_null_approximation_method (ENullApproximationMethod nmethod)
 
const ENullApproximationMethod get_null_approximation_method () const
 
void set_kernel_selection_strategy (EKernelSelectionMethod method, bool weighted=false)
 
void set_kernel_selection_strategy (EKernelSelectionMethod method, index_t num_runs, index_t num_folds, float64_t alpha)
 
void add_kernel (CKernel *kernel)
 
virtual void select_kernel ()
 
CKernelSelectionStrategy const * get_kernel_selection_strategy () const
 
virtual void set_kernel (CKernel *kernel)
 
CKernelget_kernel () const
 
virtual void set_p (CFeatures *samples_from_p)
 
CFeaturesget_p () const
 
virtual void set_q (CFeatures *samples_from_q)
 
CFeaturesget_q () const
 
void set_num_samples_p (index_t num_samples_from_p)
 
const index_t get_num_samples_p () const
 
void set_num_samples_q (index_t num_samples_from_q)
 
const index_t get_num_samples_q () const
 
CCustomDistancecompute_distance (CDistance *distance)
 
CCustomDistancecompute_joint_distance (CDistance *distance)
 
void set_train_test_mode (bool on)
 
void set_train_test_ratio (float64_t ratio)
 
bool perform_test (float64_t alpha)
 
virtual CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_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)
 
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)
 
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 >
get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
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 CSGObjectclone ()
 

Public Attributes

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

bool use_gpu () const
 
std::shared_ptr
< CKernelSelectionStrategy > 
get_strategy ()
 
internal::KernelManager & get_kernel_mgr ()
 
const internal::KernelManager & get_kernel_mgr () const
 
internal::DataManagerget_data_mgr ()
 
const internal::DataManagerget_data_mgr () const
 
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)
 
bool clone_parameters (CSGObject *other)
 

Member Typedef Documentation

typedef std::function<float32_t(SGMatrix<float32_t>)> operation

Definition at line 43 of file LinearTimeMMD.h.

Constructor & Destructor Documentation

Definition at line 45 of file LinearTimeMMD.cpp.

CLinearTimeMMD ( CFeatures samples_from_p,
CFeatures samples_from_q 
)

Definition at line 49 of file LinearTimeMMD.cpp.

~CLinearTimeMMD ( )
virtual

Definition at line 55 of file LinearTimeMMD.cpp.

Member Function Documentation

void add_kernel ( CKernel kernel)
inherited

Method that adds a kernel instance to be used for kernel selection. Please note that the kernels added by this method are NOT set as the main test kernel unless select_kernel() method is executed.

This method is NOT thread safe. Please DO NOT use this method from multiple threads.

Parameters
kernelOne of the kernel instances with which learning algorithm will work.

Definition at line 109 of file MMD.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 ( )
inherited

Definition at line 446 of file StreamingMMD.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

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

Definition at line 729 of file SGObject.cpp.

bool clone_parameters ( CSGObject other)
protectedinherited

Definition at line 754 of file SGObject.cpp.

CCustomDistance * compute_distance ( CDistance distance)
inherited

Method that pre-computes the pair-wise distance between the samples using the provided distance instance.

Parameters
distanceThe distance instance used for pre-computing the pair-wise distance.
Returns
A newly created CCustomDistance instance representing the pre-computed pair-wise distance between the samples.

Definition at line 99 of file TwoDistributionTest.cpp.

CCustomDistance * compute_joint_distance ( CDistance distance)
inherited

Method that pre-computes the pair-wise distance between the joint samples using the provided distance instance. A temporary object appending the samples from both the distributions is created in order to perform the task.

Parameters
distanceThe distance instance used for pre-computing the pair-wise distance.
Returns
A newly created CCustomDistance instance representing the pre-computed pair-wise distance between the joint samples.

Definition at line 128 of file TwoDistributionTest.cpp.

SGVector< float64_t > compute_multiple ( )
virtualinherited

Definition at line 406 of file StreamingMMD.cpp.

float64_t compute_p_value ( float64_t  statistic)
virtual

Method that computes a p-value based on current method for approximating the null-distribution. The p-value is the 1-p quantile of the null- distribution where the given statistic lies in.

This method depends on the implementation of sample_null method which should be implemented by the sub-classes.

Parameters
statisticstatistic value to compute the p-value for
Returns
p-value parameter statistic is the (1-p) percentile of the null distribution

Reimplemented from CHypothesisTest.

Definition at line 120 of file LinearTimeMMD.cpp.

float64_t compute_statistic ( )
virtualinherited

Interface for computing the test-statistic for the hypothesis test.

Returns
test statistic for the given data/parameters/methods

Implements CMMD.

Definition at line 396 of file StreamingMMD.cpp.

float64_t compute_threshold ( float64_t  alpha)
virtual

Method that computes a threshold based on current method for approximating the null-distribution. The threshold is the value that a statistic has to have in ordner to reject the null-hypothesis.

This method depends on the implementation of sample_null method which should be implemented by the sub-classes.

Parameters
alphatest level to reject null-hypothesis
Returns
Threshold for statistics to reject null-hypothesis

Reimplemented from CHypothesisTest.

Definition at line 147 of file LinearTimeMMD.cpp.

float64_t compute_variance ( )
virtualinherited

Definition at line 401 of file StreamingMMD.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 376 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 399 of file SGObject.h.

DataManager & get_data_mgr ( )
protectedinherited

Definition at line 104 of file HypothesisTest.cpp.

const DataManager & get_data_mgr ( ) const
protectedinherited

Definition at line 109 of file HypothesisTest.cpp.

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
Returns
The kernel instance that is presently being used for performing the test

Definition at line 73 of file TwoSampleTest.cpp.

KernelManager & get_kernel_mgr ( )
protectedinherited

Definition at line 83 of file TwoSampleTest.cpp.

const KernelManager & get_kernel_mgr ( ) const
protectedinherited

Definition at line 88 of file TwoSampleTest.cpp.

CKernelSelectionStrategy const * get_kernel_selection_strategy ( ) const
inherited

Method that returns the kernel selection strategy wrapper object that will be/ was used in the last kernel learning algorithm. Use this method when results of intermediate steps taken by the kernel selection algorithms are of interest.

Returns
The internal instance of CKernelSelectionStrategy that holds intermediate measures computed at the time of the last kernel selection algorithm invocation.

Definition at line 104 of file MMD.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.

const char * get_name ( ) const
virtual
Returns
The name of this class

Reimplemented from CStreamingMMD.

Definition at line 168 of file LinearTimeMMD.cpp.

const ENullApproximationMethod get_null_approximation_method ( ) const
inherited

Definition at line 492 of file StreamingMMD.cpp.

const index_t get_num_null_samples ( ) const
inherited

Definition at line 431 of file StreamingMMD.cpp.

const index_t get_num_samples_p ( ) const
inherited
Returns
The number of samples from \(\mathbf{P}\).

Definition at line 81 of file TwoDistributionTest.cpp.

const index_t get_num_samples_q ( ) const
inherited
Returns
The number of samples from \(\mathbf{Q}\).

Definition at line 93 of file TwoDistributionTest.cpp.

CFeatures * get_p ( ) const
inherited
Returns
The samples from \(\mathbf{P}\).

Definition at line 56 of file TwoDistributionTest.cpp.

CFeatures * get_q ( ) const
inherited
Returns
The samples from \(\mathbf{Q}\).

Definition at line 69 of file TwoDistributionTest.cpp.

const EStatisticType get_statistic_type ( ) const
inherited

Definition at line 457 of file StreamingMMD.cpp.

std::shared_ptr<CKernelSelectionStrategy> get_strategy ( )
protectedinherited
const EVarianceEstimationMethod get_variance_estimation_method ( ) const
inherited

Definition at line 472 of file StreamingMMD.cpp.

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 299 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 310 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 321 of file SGObject.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
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.

bool perform_test ( float64_t  alpha)
inherited

Method that performs the complete hypothesis test on current data and returns a binary answer: wheter null hypothesis is rejected or not.

This is just a wrapper for the above compute_p_value() method that returns a p-value. If this p-value lies below the test level alpha, the null hypothesis is rejected.

Should not be overwritten in subclasses. (Therefore not virtual)

Parameters
alphatest level alpha.
Returns
true if null hypothesis is rejected and false otherwise

Definition at line 92 of file HypothesisTest.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 450 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 463 of file SGObject.h.

SGVector< float64_t > sample_null ( )
virtualinherited

Interface for computing the samples under the null-hypothesis.

Returns
vector of all statistics

Implements CMMD.

Definition at line 421 of file StreamingMMD.cpp.

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 select_kernel ( )
virtualinherited

Method that selects/learns the kernel based on the defined kernel selection strategy. If no explicit kernel selection strategy was set using set_kernel_selection_strategy() method, then a default strategy is used. Please see EKernelSelectionMethod for the default strategy.

This method is NOT thread safe. It replaces the internel kernel set by set_kernel() method, if there was any. Please DO NOT use this method from multiple threads.

The learned/selected kernel can be obtained from a subsequent get_kernel() call.

This method expects train-test mode to be turned on at the time of invocation. Please see the class documentation of CHypothesisTest.

Reimplemented in CQuadraticTimeMMD.

Definition at line 114 of file MMD.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 337 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 363 of file SGObject.h.

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)
virtualinherited

Method that sets the kernel that is used for performing the two-sample test. It is kept virtual so that sub-classes can perform other initialization tasks that has to be trigger every time a kernel is set/updated.

Parameters
kernelThe kernel instance.

Reimplemented in CQuadraticTimeMMD.

Definition at line 66 of file TwoSampleTest.cpp.

void set_kernel_selection_strategy ( EKernelSelectionMethod  method,
bool  weighted = false 
)
inherited

Method that sets the specific kernel selection strategy based on the specific parameters provided. Please see class documentation for details. Use this method for every other strategy other than KSM_CROSS_VALIDATION.

Parameters
methodThe kernel selection method as specified in EKernelSelectionMethod.
weightedIf true, then an weighted combination of the kernel is used after solving an optimization. If false, only a single kernel is selected among the provided ones.

Definition at line 89 of file MMD.cpp.

void set_kernel_selection_strategy ( EKernelSelectionMethod  method,
index_t  num_runs,
index_t  num_folds,
float64_t  alpha 
)
inherited

Method that sets the specific kernel selection strategy based on the specific parameters provided. Please see class documentation for details. Use this method for KSM_CROSS_VALIDATION.

Parameters
methodThe kernel selection method as specified in EKernelSelectionMethod.
num_runsThe number of total runs of the cross-validation algorithm.
num_foldsThe number of folds (k) to be used in k-fold stratified cross-validation.
alphaThe threshold to be used while performing test for the test-folds.

Definition at line 95 of file MMD.cpp.

void set_null_approximation_method ( ENullApproximationMethod  nmethod)
inherited

Definition at line 477 of file StreamingMMD.cpp.

void set_num_blocks_per_burst ( index_t  num_blocks_per_burst)

Definition at line 59 of file LinearTimeMMD.cpp.

void set_num_null_samples ( index_t  null_samples)
inherited

Definition at line 426 of file StreamingMMD.cpp.

void set_num_samples_p ( index_t  num_samples_from_p)
inherited

Method that initializes the number of samples to be drawn from distribution \(\mathbf{P}\). Please ensure to call this method if you are intending to use streaming data generators that generate the samples on the fly. For other types of features, the number of samples is set internally from the features object itself, therefore this method should not be used.

Parameters
num_samples_from_pThe CFeatures instance representing the samples from \(\mathbf{P}\).

Definition at line 75 of file TwoDistributionTest.cpp.

void set_num_samples_q ( index_t  num_samples_from_q)
inherited

Method that initializes the number of samples to be drawn from distribution \(\mathbf{Q}\). Please ensure to call this method if you are intending to use streaming data generators that generate the samples on the fly. For other types of features, the number of samples is set internally from the features object itself, therefore this method should not be used.

Parameters
num_samples_from_qThe CFeatures instance representing the samples from \(\mathbf{Q}\).

Definition at line 87 of file TwoDistributionTest.cpp.

void set_p ( CFeatures samples_from_p)
virtualinherited

Method that initializes the samples from \(\mathbf{P}\). This method is kept virtual for the sub-classes to perform additional initialization tasks that have to be performed every time features are set/updated.

Parameters
samples_from_pThe CFeatures instance representing the samples from \(\mathbf{P}\).

Reimplemented in CQuadraticTimeMMD.

Definition at line 49 of file TwoDistributionTest.cpp.

void set_q ( CFeatures samples_from_q)
virtualinherited

Method that initializes the samples from \(\mathbf{Q}\). This method is kept virtual for the sub-classes to perform additional initialization tasks that have to be performed every time features are set/updated.

Parameters
samples_from_qThe CFeatures instance representing the samples from \(\mathbf{Q}\).

Reimplemented in CQuadraticTimeMMD.

Definition at line 62 of file TwoDistributionTest.cpp.

void set_statistic_type ( EStatisticType  stype)
inherited

Definition at line 452 of file StreamingMMD.cpp.

void set_train_test_mode ( bool  on)
inherited

Method that enables/disables the training-testing mode. If this option is turned on, then the samples would be split in two pieces: one chunk would be used for training algorithms and the other chunk would be used for performing tests. If this option is turned off, the entire data would be used for performing the test. Before running any training algorithms, make sure to turn this mode on.

By default, the training-testing mode is turned off.

See also
{set_train_test_ratio()}
Parameters
onWhether to enable/disable the training-testing mode

Definition at line 66 of file HypothesisTest.cpp.

void set_train_test_ratio ( float64_t  ratio)
inherited

Method that specifies the ratio of training-testing data split for the algorithms. Note that this is NOT the percentage of samples to be used for training, rather the ratio of the number of samples to be used for training and that of testing.

By default, an equal 50-50 split (ratio = 1) is made.

See also
{set_train_test_mode()}
Parameters
ratioThe ratio of the number of samples to be used for training and that of testing

Definition at line 71 of file HypothesisTest.cpp.

void set_variance_estimation_method ( EVarianceEstimationMethod  vmethod)
inherited

Definition at line 462 of file StreamingMMD.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.

void use_gpu ( bool  gpu)
inherited

Definition at line 436 of file StreamingMMD.cpp.

bool use_gpu ( ) const
protectedinherited

Definition at line 441 of file StreamingMMD.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 558 of file SGObject.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 573 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 576 of file SGObject.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 570 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 567 of file SGObject.h.

Parallel* parallel
inherited

parallel

Definition at line 561 of file SGObject.h.

Version* version
inherited

version

Definition at line 564 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation