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CLinearTimeMMD类 参考

详细描述

This class implements the linear time Maximum Mean Statistic as described in [1]. This statistic is in particular suitable for streaming data. Therefore, only streaming features may be passed. To process other feature types, construct streaming features from these (see constructor documentations). A blocksize has to be specified that determines how many examples are processed at once. This should be set as large as available memory allows to ensure faster computations.

The MMD is the distance of two probability distributions \(p\) and \(q\) in a RKHS.

\[ \text{MMD}}[\mathcal{F},p,q]^2=\textbf{E}_{x,x'}\left[ k(x,x')\right]- 2\textbf{E}_{x,y}\left[ k(x,y)\right] +\textbf{E}_{y,y'}\left[ k(y,y')\right]=||\mu_p - \mu_q||^2_\mathcal{F} \]

Given two sets of samples \(\{x_i\}_{i=1}^m\sim p\) and \(\{y_i\}_{i=1}^n\sim q\) the (unbiased) statistic is computed as

\[ \text{MMD}_l^2[\mathcal{F},X,Y]=\frac{1}{m_2}\sum_{i=1}^{m_2} h(z_{2i},z_{2i+1}) \]

where

\[ h(z_{2i},z_{2i+1})=k(x_{2i},x_{2i+1})+k(y_{2i},y_{2i+1})-k(x_{2i},y_{2i+1})- k(x_{2i+1},y_{2i}) \]

and \( m_2=\lfloor\frac{m}{2} \rfloor\).

Along with the statistic comes a method to compute a p-value based on a Gaussian approximation of the null-distribution which is also possible in linear time and constant space. Bootstrapping, is also possible (no permutations but new examples will be used here). If unsure which one to use, bootstrapping with 250 iterations always is correct (but slow). When the sample size is large (>1000) at least, the Gaussian approximation is an accurate and much faster choice than bootstrapping.

To choose, use set_null_approximation_method() and choose from

MMD1_GAUSSIAN: Approximates the null-distribution with a Gaussian. Only use from at least 1000 samples. If using, check if type I error equals the desired value.

BOOTSTRAPPING: For permuting available samples to sample null-distribution

For kernel selection see CMMDKernelSelection.

[1]: Gretton, A., Borgwardt, K. M., Rasch, M. J., Schoelkopf, B., & Smola, A. (2012). A Kernel Two-Sample Test. Journal of Machine Learning Research, 13, 671-721.

在文件 LinearTimeMMD.h75 行定义.

类 CLinearTimeMMD 继承关系图:
Inheritance graph
[图例]

Public 成员函数

 CLinearTimeMMD ()
 
 CLinearTimeMMD (CKernel *kernel, CStreamingFeatures *p, CStreamingFeatures *q, index_t m, index_t blocksize=10000)
 
virtual ~CLinearTimeMMD ()
 
virtual float64_t compute_statistic ()
 
virtual SGVector< float64_tcompute_statistic (bool multiple_kernels)
 
virtual float64_t compute_p_value (float64_t statistic)
 
virtual float64_t perform_test ()
 
virtual float64_t compute_threshold (float64_t alpha)
 
virtual float64_t compute_variance_estimate ()
 
virtual void compute_statistic_and_variance (SGVector< float64_t > &statistic, SGVector< float64_t > &variance, bool multiple_kernels=false)
 
virtual void compute_statistic_and_Q (SGVector< float64_t > &statistic, SGMatrix< float64_t > &Q)
 
virtual SGVector< float64_tbootstrap_null ()
 
void set_blocksize (index_t blocksize)
 
virtual void set_p_and_q (CFeatures *p_and_q)
 
virtual CFeaturesget_p_and_q ()
 
virtual CStreamingFeaturesget_streaming_p ()
 
virtual CStreamingFeaturesget_streaming_q ()
 
virtual EStatisticType get_statistic_type () const
 
void set_simulate_h0 (bool simulate_h0)
 
virtual const char * get_name () const
 
virtual void set_kernel (CKernel *kernel)
 
virtual CKernelget_kernel ()
 
index_t get_m ()
 
bool perform_test (float64_t alpha)
 
virtual void set_bootstrap_iterations (index_t bootstrap_iterations)
 
virtual void set_null_approximation_method (ENullApproximationMethod null_approximation_method)
 
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="", int32_t param_version=Version::get_version_parameter())
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
 
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
 
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
 
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
 
void set_global_io (SGIO *io)
 
SGIOget_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallelget_global_parallel ()
 
void set_global_version (Version *version)
 
Versionget_global_version ()
 
SGStringList< char > get_modelsel_names ()
 
void print_modsel_params ()
 
char * get_modsel_param_descr (const char *param_name)
 
index_t get_modsel_param_index (const char *param_name)
 
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
 
virtual bool update_parameter_hash ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0)
 
virtual CSGObjectclone ()
 

Public 属性

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
ParameterMapm_parameter_map
 
uint32_t m_hash
 

Protected 成员函数

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 属性

CStreamingFeaturesm_streaming_p
 
CStreamingFeaturesm_streaming_q
 
index_t m_blocksize
 
bool m_simulate_h0
 
CKernelm_kernel
 
CFeaturesm_p_and_q
 
index_t m_m
 
index_t m_bootstrap_iterations
 
ENullApproximationMethod m_null_approximation_method
 

构造及析构函数说明

在文件 LinearTimeMMD.cpp22 行定义.

CLinearTimeMMD ( CKernel kernel,
CStreamingFeatures p,
CStreamingFeatures q,
index_t  m,
index_t  blocksize = 10000 
)

Constructor.

参数
kernelkernel to use
pstreaming features p to use
qstreaming features q to use
mindex of first sample of q
blocksizesize of examples that are processed at once when computing statistic/threshold. If larger than m/2, all examples will be processed at once. Memory consumption increased linearly in the blocksize. Choose as large as possible regarding available memory.

在文件 LinearTimeMMD.cpp28 行定义.

~CLinearTimeMMD ( )
virtual

在文件 LinearTimeMMD.cpp43 行定义.

成员函数说明

SGVector< float64_t > bootstrap_null ( )
virtual

Mimics bootstrapping for the linear time MMD. However, samples are not permutated but constantly streamed and then merged. Usually, this is not necessary since there is the Gaussian approximation for the null distribution. However, in certain cases this may fail and sampling the null distribution might be numerically more stable. Ovewrite superclass method that merges samples.

返回
vector of all statistics

重载 CKernelTwoSampleTestStatistic .

在文件 LinearTimeMMD.cpp683 行定义.

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.

参数
dictdictionary of parameters to be built.

在文件 SGObject.cpp1156 行定义.

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.

返回
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

在文件 SGObject.cpp1273 行定义.

float64_t compute_p_value ( float64_t  statistic)
virtual

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.

The method for computing the p-value can be set via set_null_approximation_method(). Since the null- distribution is normal, a Gaussian approximation is available.

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

重载 CTwoDistributionsTestStatistic .

在文件 LinearTimeMMD.cpp608 行定义.

float64_t compute_statistic ( )
virtual

Computes the squared linear time MMD for the current data. This is an unbiased estimate.

Note that the underlying streaming feature parser has to be started before this is called. Otherwise deadlock.

返回
squared linear time MMD

实现了 CKernelTwoSampleTestStatistic.

在文件 LinearTimeMMD.cpp573 行定义.

SGVector< float64_t > compute_statistic ( bool  multiple_kernels)
virtual

Same as compute_statistic(), but with the possibility to perform on multiple kernels at once

参数
multiple_kernelsif true, and underlying kernel is K_COMBINED, method will be executed on all subkernels on the same data
返回
vector of results for subkernels

实现了 CKernelTwoSampleTestStatistic.

在文件 LinearTimeMMD.cpp583 行定义.

void compute_statistic_and_Q ( SGVector< float64_t > &  statistic,
SGMatrix< float64_t > &  Q 
)
virtual

Same as compute_statistic_and_variance, but computes a linear time estimate of the covariance of the multiple-kernel-MMD. See [1] for details.

在文件 LinearTimeMMD.cpp274 行定义.

void compute_statistic_and_variance ( SGVector< float64_t > &  statistic,
SGVector< float64_t > &  variance,
bool  multiple_kernels = false 
)
virtual

Computes MMD and a linear time variance estimate. If multiple_kernels is set to true, each subkernel is evaluated on the same data.

参数
statisticreturn parameter for statistic, vector with entry for each kernel. May be allocated before but doesn not have to be
variancereturn parameter for statistic, vector with entry for each kernel. May be allocated before but doesn not have to be
multiple_kernelsoptional flag, if set to true, it is assumed that the underlying kernel is of type K_COMBINED. Then, the MMD is computed on all subkernel separately rather than computing it on the combination. This is used by kernel selection strategies that need to evaluate multiple kernels on the same data. Since the linear time MMD works on streaming data, one cannot simply compute MMD, change kernel since data would be different for every kernel.

在文件 LinearTimeMMD.cpp68 行定义.

float64_t compute_threshold ( float64_t  alpha)
virtual

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.

The method for computing the p-value can be set via set_null_approximation_method(). Since the null- distribution is normal, a Gaussian approximation is available.

参数
alphatest level to reject null-hypothesis
返回
threshold for statistics to reject null-hypothesis

重载 CTwoDistributionsTestStatistic .

在文件 LinearTimeMMD.cpp631 行定义.

float64_t compute_variance_estimate ( )
virtual

computes a linear time estimate of the variance of the squared linear time mmd, which may be used for an approximation of the null-distribution The value is the variance of the vector of which the linear time MMD is the mean.

返回
variance estimate

在文件 LinearTimeMMD.cpp598 行定义.

virtual CSGObject* deep_copy ( ) const
virtualinherited

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

在文件 SGObject.h126 行定义.

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

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

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

参数
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
返回
true if all parameters were equal, false if not

在文件 SGObject.cpp1177 行定义.

SGIO * get_global_io ( )
inherited

get the io object

返回
io object

在文件 SGObject.cpp174 行定义.

Parallel * get_global_parallel ( )
inherited

get the parallel object

返回
parallel object

在文件 SGObject.cpp209 行定义.

Version * get_global_version ( )
inherited

get the version object

返回
version object

在文件 SGObject.cpp222 行定义.

virtual CKernel* get_kernel ( )
virtualinherited
返回
underlying kernel, is SG_REF'ed

在文件 KernelTwoSampleTestStatistic.h80 行定义.

index_t get_m ( )
inherited
返回
number of to be used samples m

在文件 TwoDistributionsTestStatistic.h98 行定义.

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

在文件 SGObject.cpp1060 行定义.

char * get_modsel_param_descr ( const char *  param_name)
inherited

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

参数
param_namename of the parameter
返回
description of the parameter

在文件 SGObject.cpp1084 行定义.

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

参数
param_namename of model selection parameter
返回
index of model selection parameter with provided name, -1 if there is no such

在文件 SGObject.cpp1097 行定义.

virtual const char* get_name ( ) const
virtual

Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.

返回
name of the SGSerializable

实现了 CKernelTwoSampleTestStatistic.

在文件 LinearTimeMMD.h242 行定义.

CFeatures * get_p_and_q ( )
virtual

Not implemented for linear time MMD since it uses streaming feautres

重载 CTwoDistributionsTestStatistic .

在文件 LinearTimeMMD.cpp715 行定义.

virtual EStatisticType get_statistic_type ( ) const
virtual

returns the statistic type of this test statistic

实现了 CTestStatistic.

在文件 LinearTimeMMD.h231 行定义.

CStreamingFeatures * get_streaming_p ( )
virtual

Getter for streaming features of p distribution.

返回
streaming features object for p distribution, SG_REF'ed

在文件 LinearTimeMMD.cpp722 行定义.

CStreamingFeatures * get_streaming_q ( )
virtual

Getter for streaming features of q distribution.

返回
streaming features object for q distribution, SG_REF'ed

在文件 LinearTimeMMD.cpp728 行定义.

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.

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

在文件 SGObject.cpp228 行定义.

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)

参数
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
返回
(sorted) array of created TParameter instances with file data

在文件 SGObject.cpp633 行定义.

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

参数
param_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
返回
new array with TParameter instances with the attached data

在文件 SGObject.cpp474 行定义.

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!

参数
filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
返回
TRUE if done, otherwise FALSE

在文件 SGObject.cpp305 行定义.

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CWeightedDegreePositionStringKernel, CKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.

在文件 SGObject.cpp989 行定义.

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp984 行定义.

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

参数
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

在文件 SGObject.cpp671 行定义.

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

参数
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
返回
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

在文件 SGObject.cpp878 行定义.

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)

参数
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

在文件 SGObject.cpp818 行定义.

bool perform_test ( float64_t  alpha)
inherited

Performs the complete two-sample test on current data and returns a binary answer wheter null hypothesis is rejected or not.

This is just a wrapper for the above perform_test() 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)

参数
alphatest level alpha.
返回
true if null hypothesis is rejected and false otherwise

在文件 TestStatistic.cpp58 行定义.

float64_t perform_test ( )
virtual

Performs the complete two-sample test on current data and returns a p-value.

In case null distribution should be estimated with MMD1_GAUSSIAN, statistic and p-value are computed in the same loop, which is more efficient than first computing statistic and then computung p-values.

In case of bootstrapping, superclass method is called.

The method for computing the p-value can be set via set_null_approximation_method().

返回
p-value such that computed statistic is the (1-p) quantile of the estimated null distribution

重载 CTestStatistic .

在文件 LinearTimeMMD.cpp654 行定义.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

在文件 SGObject.cpp1036 行定义.

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

prints registered parameters out

参数
prefixprefix for members

在文件 SGObject.cpp240 行定义.

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

Save this object to file.

参数
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)
返回
TRUE if done, otherwise FALSE

在文件 SGObject.cpp246 行定义.

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CKernel 重载.

在文件 SGObject.cpp999 行定义.

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp994 行定义.

void set_blocksize ( index_t  blocksize)

Setter for the blocksize of examples to be processed at once

参数
blocksizenew blocksize to use

在文件 LinearTimeMMD.h212 行定义.

void set_bootstrap_iterations ( index_t  bootstrap_iterations)
virtualinherited

sets the number of bootstrap iterations for bootstrap_null()

参数
bootstrap_iterationshow often bootstrapping shall be done

在文件 TestStatistic.cpp44 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp41 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp46 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp51 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp56 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp61 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp66 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp71 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp76 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp81 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp86 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp91 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp96 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp101 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp106 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp111 行定义.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO io)
inherited

set the io object

参数
ioio object to use

在文件 SGObject.cpp167 行定义.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

参数
parallelparallel object to use

在文件 SGObject.cpp180 行定义.

void set_global_version ( Version version)
inherited

set the version object

参数
versionversion object to use

在文件 SGObject.cpp215 行定义.

virtual void set_kernel ( CKernel kernel)
virtualinherited

Setter for the underlying kernel

参数
kernelnew kernel to use

在文件 KernelTwoSampleTestStatistic.h71 行定义.

void set_null_approximation_method ( ENullApproximationMethod  null_approximation_method)
virtualinherited

sets the method how to approximate the null-distribution

参数
null_approximation_methodmethod to use

在文件 TestStatistic.cpp38 行定义.

void set_p_and_q ( CFeatures p_and_q)
virtual

Not implemented for linear time MMD since it uses streaming feautres

重载 CTwoDistributionsTestStatistic .

在文件 LinearTimeMMD.cpp709 行定义.

void set_simulate_h0 ( bool  simulate_h0)
参数
simulate_h0if true, samples from p and q will be mixed and permuted

在文件 LinearTimeMMD.h239 行定义.

virtual CSGObject* shallow_copy ( ) const
virtualinherited

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

CGaussianKernel 重载.

在文件 SGObject.h117 行定义.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

在文件 SGObject.cpp235 行定义.

bool update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination.

返回
bool if parameter combination has changed since last update.

在文件 SGObject.cpp187 行定义.

类成员变量说明

SGIO* io
inherited

io

在文件 SGObject.h473 行定义.

index_t m_blocksize
protected

Number of examples processed at once, i.e. in one burst

在文件 LinearTimeMMD.h258 行定义.

index_t m_bootstrap_iterations
protectedinherited

number of iterations for bootstrapping null-distributions

在文件 TestStatistic.h138 行定义.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

在文件 SGObject.h488 行定义.

uint32_t m_hash
inherited

Hash of parameter values

在文件 SGObject.h494 行定义.

CKernel* m_kernel
protectedinherited

underlying kernel

在文件 KernelTwoSampleTestStatistic.h115 行定义.

index_t m_m
protectedinherited

defines the first index of samples of q

在文件 TwoDistributionsTestStatistic.h110 行定义.

Parameter* m_model_selection_parameters
inherited

model selection parameters

在文件 SGObject.h485 行定义.

ENullApproximationMethod m_null_approximation_method
protectedinherited

Defines how the the null distribution is approximated

在文件 TestStatistic.h141 行定义.

CFeatures* m_p_and_q
protectedinherited

concatenated samples of the two distributions (two blocks)

在文件 TwoDistributionsTestStatistic.h107 行定义.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

在文件 SGObject.h491 行定义.

Parameter* m_parameters
inherited

parameters

在文件 SGObject.h482 行定义.

bool m_simulate_h0
protected

If this is true, samples will be mixed between p and q ind any method that computes the statistic

在文件 LinearTimeMMD.h262 行定义.

CStreamingFeatures* m_streaming_p
protected

Streaming feature objects that are used instead of merged samples

在文件 LinearTimeMMD.h252 行定义.

CStreamingFeatures* m_streaming_q
protected

Streaming feature objects that are used instead of merged samples

在文件 LinearTimeMMD.h255 行定义.

Parallel* parallel
inherited

parallel

在文件 SGObject.h476 行定义.

Version* version
inherited

version

在文件 SGObject.h479 行定义.


该类的文档由以下文件生成:

SHOGUN Machine Learning Toolbox - Documentation