SHOGUN  6.1.3
CRandomKitchenSinksDotFeatures Class Referenceabstract

## Detailed Description

class that implements the Random Kitchen Sinks (RKS) for the DotFeatures as mentioned in http://books.nips.cc/papers/files/nips21/NIPS2008_0885.pdf.

RKS input:

• a dataset $$\{x_i, y_i\}_{i=1,\dots,m}$$ of $$m$$ points to work on
• $$\phi(x; w)$$: a bounded feature function s.t. $$|\phi(x; w)| \leq 1$$, where $$w$$ is the function parameter
• $$p(w)$$: a probability distrubution function, from which to draw the $$w$$
• $$K$$: the number of samples to draw from $$p(w)$$
• $$C$$: a scalar, which is chosen to be large enough in practice.

RKS output: A function $$\hat{f}(x) = \sum_{k=1}^{K} \phi(x; w_k)\alpha_k$$ 1. Draw $$w_1,\dots,w_K$$ iid from $$p(w)$$ 2. Featurize the input: $$z_i = [\phi(x_i; w_1),\dots,\phi(x_i; w_K)]^{\top}$$ 3. With $$w$$ fixed, solve the empirical risk minimization problem:

$\underset{\alpha \in \mathbf{R}^K}{\text{minimize}} \quad \frac{1}{m}\sum_{i=1}^{m} c(\alpha^{\top} z_i, y_i)$

$\text{s.t.} \quad \|\alpha\|_{\infty} \leq C/K.$

for vector $$\alpha$$, either through least squares when $$c(y', y)$$ is the quadratic loss or through a linear SVM when $$c(y', y)$$ is the hinge loss.

This class implements the vector transformation on-the-fly whenever it is needed. In order for it to work, the class expects the user to implement a subclass of CRKSFunctions and implement in there the functions $$\phi$$ and $$p$$ and then pass an instantiated object of that class to the constructor. For example, in the derived class CRandomFourierDotFeatures, random fourier features are implemented as $$z(x) = \sqrt{2/K}\cos(w^{\top}x + b)$$, where $$w$$ drawn from a Gaussian distribution and $$b$$ from a uniform distribution.

Further useful resources, include : http://www.shloosl.com/~ali/random-features/ https://research.microsoft.com/apps/video/dl.aspx?id=103390&l=i

Definition at line 50 of file RandomKitchenSinksDotFeatures.h.

Inheritance diagram for CRandomKitchenSinksDotFeatures:
[legend]

## Public Types

typedef rxcpp::subjects::subject< ObservedValueSGSubject

typedef rxcpp::observable< ObservedValue, rxcpp::dynamic_observable< ObservedValue > > SGObservable

typedef rxcpp::subscriber< ObservedValue, rxcpp::observer< ObservedValue, void, void, void, void > > SGSubscriber

## Public Member Functions

CRandomKitchenSinksDotFeatures ()

CRandomKitchenSinksDotFeatures (CDotFeatures *dataset, int32_t K)

CRandomKitchenSinksDotFeatures (CDotFeatures *dataset, int32_t K, SGMatrix< float64_t > coeff)

CRandomKitchenSinksDotFeatures (const CRandomKitchenSinksDotFeatures &orig)

virtual CFeaturesduplicate () const

virtual ~CRandomKitchenSinksDotFeatures ()

virtual int32_t get_dim_feature_space () const

virtual float64_t dot (int32_t vec_idx1, CDotFeatures *df, int32_t vec_idx2)

virtual float64_t dense_dot (int32_t vec_idx1, const float64_t *vec2, int32_t vec2_len)

virtual void add_to_dense_vec (float64_t alpha, int32_t vec_idx1, float64_t *vec2, int32_t vec2_len, bool abs_val=false)

virtual int32_t get_nnz_features_for_vector (int32_t num)

virtual void * get_feature_iterator (int32_t vector_index)

virtual bool get_next_feature (int32_t &index, float64_t &value, void *iterator)

virtual void free_feature_iterator (void *iterator)

virtual EFeatureType get_feature_type () const

virtual EFeatureClass get_feature_class () const

virtual int32_t get_num_vectors () const

SGMatrix< float64_tgenerate_random_coefficients ()

SGMatrix< float64_tget_random_coefficients ()

const char * get_name () const

virtual float64_t dense_dot_sgvec (int32_t vec_idx1, const SGVector< float64_t > vec2)

virtual void dense_dot_range (float64_t *output, int32_t start, int32_t stop, float64_t *alphas, float64_t *vec, int32_t dim, float64_t b)

virtual void dense_dot_range_subset (int32_t *sub_index, int32_t num, float64_t *output, float64_t *alphas, float64_t *vec, int32_t dim, float64_t b)

float64_t get_combined_feature_weight ()

void set_combined_feature_weight (float64_t nw)

SGMatrix< float64_tget_computed_dot_feature_matrix ()

SGVector< float64_tget_computed_dot_feature_vector (int32_t num)

void benchmark_dense_dot_range (int32_t repeats=5)

virtual SGVector< float64_tget_mean ()

virtual SGMatrix< float64_tget_cov (bool copy_data_for_speed=true)

virtual Range< int32_t > index_iterator () const

virtual void del_preprocessor (int32_t num)

CPreprocessorget_preprocessor (int32_t num) const

void set_preprocessed (int32_t num)

bool is_preprocessed (int32_t num) const

int32_t get_num_preprocessed () const

int32_t get_num_preprocessors () const

void clean_preprocessors ()

void list_preprocessors ()

int32_t get_cache_size () const

virtual bool reshape (int32_t num_features, int32_t num_vectors)

void list_feature_obj () const

virtual void save (CFile *writer)

bool check_feature_compatibility (CFeatures *f) const

bool has_property (EFeatureProperty p) const

void set_property (EFeatureProperty p)

void unset_property (EFeatureProperty p)

virtual CFeaturescreate_merged_copy (CList *others)

virtual CFeaturescreate_merged_copy (CFeatures *other)

virtual void add_subset (SGVector< index_t > subset)

virtual void add_subset_in_place (SGVector< index_t > subset)

virtual void remove_subset ()

virtual void remove_all_subsets ()

virtual CSubsetStackget_subset_stack ()

virtual void subset_changed_post ()

virtual CFeaturescopy_subset (SGVector< index_t > indices)

virtual CFeaturescopy_dimension_subset (SGVector< index_t > dims)

virtual bool support_compatible_class () const

virtual bool get_feature_class_compatibility (EFeatureClass rhs) const

virtual CFeaturesshallow_subset_copy ()

int32_t ref ()

int32_t ref_count ()

int32_t unref ()

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

SGObservableget_parameters_observable ()

void subscribe_to_parameters (ParameterObserverInterface *obs)

void list_observable_parameters ()

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 ()

## Static Public Member Functions

static SGVector< float64_tcompute_mean (CDotFeatures *lhs, CDotFeatures *rhs)

static SGMatrix< float64_tcompute_cov (CDotFeatures *lhs, CDotFeatures *rhs, bool copy_data_for_speed=true)

## Public Attributes

SGIOio

Parallelparallel

Versionversion

Parameterm_parameters

Parameterm_model_selection_parameters

uint32_t m_hash

## Protected Member Functions

virtual float64_t dot (index_t vec_idx, index_t par_idx)

virtual float64_t post_dot (float64_t dot_result, index_t par_idx)

virtual SGVector< float64_tgenerate_random_parameter_vector ()=0

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)

void observe (const ObservedValue value)

void register_observable_param (const std::string &name, const SG_OBS_VALUE_TYPE type, const std::string &description)

## Protected Attributes

CDotFeaturesfeats

int32_t num_samples

SGMatrix< float64_trandom_coeff

float64_t combined_weight
feature weighting in combined dot features More...

CSubsetStackm_subset_stack

## Member Typedef Documentation

 inherited

Definition at line 130 of file SGObject.h.

 inherited

Definition at line 127 of file SGObject.h.

 typedef rxcpp::subscriber< ObservedValue, rxcpp::observer > SGSubscriber
inherited

Definition at line 133 of file SGObject.h.

## Constructor & Destructor Documentation

 CRandomKitchenSinksDotFeatures ( )

default constructor

Definition at line 20 of file RandomKitchenSinksDotFeatures.cpp.

 CRandomKitchenSinksDotFeatures ( CDotFeatures * dataset, int32_t K )

constructor Subclasses should call generate_random_coefficients() on their own if they choose to use this constructor.

Parameters
 dataset the dataset to work on K the number of samples to draw

Definition at line 26 of file RandomKitchenSinksDotFeatures.cpp.

 CRandomKitchenSinksDotFeatures ( CDotFeatures * dataset, int32_t K, SGMatrix< float64_t > coeff )

constructor

Parameters
 dataset the dataset to work on K the number of samples to draw coeff the random coefficients to use

Definition at line 32 of file RandomKitchenSinksDotFeatures.cpp.

 CRandomKitchenSinksDotFeatures ( CFile * loader )

Parameters

Definition at line 55 of file RandomKitchenSinksDotFeatures.cpp.

 CRandomKitchenSinksDotFeatures ( const CRandomKitchenSinksDotFeatures & orig )

copy constructor

Definition at line 60 of file RandomKitchenSinksDotFeatures.cpp.

 ~CRandomKitchenSinksDotFeatures ( )
virtual

destructor

Definition at line 67 of file RandomKitchenSinksDotFeatures.cpp.

## Member Function Documentation

 void add_preprocessor ( CPreprocessor * p )
virtualinherited

Parameters
 p preprocessor to set

Definition at line 85 of file Features.cpp.

 void add_subset ( SGVector< index_t > subset )
virtualinherited

Adds a subset of indices on top of the current subsets (possibly subset of subset). Every call causes a new active index vector to be stored. Added subsets can be removed one-by-one. If this is not needed, add_subset_in_place() should be used (does not store intermediate index vectors)

Calls subset_changed_post() afterwards

Parameters
 subset subset of indices to add

Reimplemented in CCombinedFeatures.

Definition at line 310 of file Features.cpp.

 void add_subset_in_place ( SGVector< index_t > subset )
virtualinherited

Sets/changes latest added subset. This allows to add multiple subsets with in-place memory requirements. They cannot be removed one-by-one afterwards, only the latest active can. If this is needed, use add_subset(). If no subset is active, this just adds.

Calls subset_changed_post() afterwards

Parameters
 subset subset of indices to replace the latest one with.

Definition at line 316 of file Features.cpp.

 void add_to_dense_vec ( float64_t alpha, int32_t vec_idx1, float64_t * vec2, int32_t vec2_len, bool abs_val = false )
virtual

add vector 1 multiplied with alpha to dense vector2

possible with subset

Parameters
 alpha scalar alpha vec_idx1 index of first vector vec2 pointer to real valued vector vec2_len length of real valued vector abs_val if true add the absolute value

Implements CDotFeatures.

Definition at line 127 of file RandomKitchenSinksDotFeatures.cpp.

 void benchmark_add_to_dense_vector ( int32_t repeats = 5 )
inherited

Definition at line 187 of file DotFeatures.cpp.

 void benchmark_dense_dot_range ( int32_t repeats = 5 )
inherited

run benchmark for dense_dot_range

Definition at line 210 of file DotFeatures.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
 dict dictionary of parameters to be built.

Definition at line 635 of file SGObject.cpp.

 bool check_feature_compatibility ( CFeatures * f ) const
inherited

check feature compatibility

Parameters
 f features to check for compatibility
Returns
if features are compatible

Definition at line 283 of file Features.cpp.

 void clean_preprocessors ( )
inherited

clears all preprocs

Definition at line 116 of file Features.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 734 of file SGObject.cpp.

 bool clone_parameters ( CSGObject * other )
protectedinherited

Definition at line 759 of file SGObject.cpp.

 SGMatrix< float64_t > compute_cov ( CDotFeatures * lhs, CDotFeatures * rhs, bool copy_data_for_speed = true )
staticinherited

compute the covariance of two CDotFeatures together

Parameters
 copy_data_for_speed
CDotFeatures::get_cov
Returns
covariance

Definition at line 342 of file DotFeatures.cpp.

 SGVector< float64_t > compute_mean ( CDotFeatures * lhs, CDotFeatures * rhs )
staticinherited

get mean of two CDotFeature objects

Returns
mean returned

Definition at line 272 of file DotFeatures.cpp.

 CFeatures * copy_dimension_subset ( SGVector< index_t > dims )
virtualinherited

Creates a new CFeatures instance containing only the dimensions of the feature vector which are specified by the provided indices.

This method is needed for feature selection tasks NOT IMPLEMENTED!

Parameters
 dims indices of feature dimensions to copy
Returns
new CFeatures instance with copies of specified features

Definition at line 348 of file Features.cpp.

 CFeatures * copy_subset ( SGVector< index_t > indices )
virtualinherited

Creates a new CFeatures instance containing copies of the elements which are specified by the provided indices.

This method is needed for a KernelMachine to store its model data. NOT IMPLEMENTED!

Parameters
 indices indices of feature elements to copy
Returns
new CFeatures instance with copies of feature data

Definition at line 340 of file Features.cpp.

 virtual CFeatures* create_merged_copy ( CList * others )
virtualinherited

Takes a list of feature instances and returns a new instance being a concatenation of a copy of this instace's data and the given instancess data. Note that the feature types have to be equal.

NOT IMPLEMENTED!

Parameters
 others list of feature objects to append
Returns
new feature object which contains copy of data of this instance and given ones

Definition at line 252 of file Features.h.

 virtual CFeatures* create_merged_copy ( CFeatures * other )
virtualinherited

Convenience method for method with same name and list as parameter.

NOT IMPLEMENTED!

Parameters
 other feature object to append
Returns
new feature object which contains copy of data of this instance and of given one

Definition at line 266 of file Features.h.

 CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 232 of file SGObject.cpp.

 void del_preprocessor ( int32_t num )
virtualinherited

delete preprocessor from list

Parameters
 num index of preprocessor in list

Definition at line 122 of file Features.cpp.

 float64_t dense_dot ( int32_t vec_idx1, const float64_t * vec2, int32_t vec2_len )
virtual

compute dot product between vector1 and a dense vector

possible with subset

Parameters
 vec_idx1 index of first vector vec2 pointer to real valued vector vec2_len length of real valued vector

Implements CDotFeatures.

Definition at line 110 of file RandomKitchenSinksDotFeatures.cpp.

 void dense_dot_range ( float64_t * output, int32_t start, int32_t stop, float64_t * alphas, float64_t * vec, int32_t dim, float64_t b )
virtualinherited

Compute the dot product for a range of vectors. This function makes use of dense_dot alphas[i] * sparse[i]^T * w + b

Parameters
 output result for the given vector range start start vector range from this idx stop stop vector range at this idx alphas scalars to multiply with, may be NULL vec dense vector to compute dot product with dim length of the dense vector b bias

note that the result will be written to output[0...(stop-start-1)]

Reimplemented in CCombinedDotFeatures, and CHashedWDFeaturesTransposed.

Definition at line 53 of file DotFeatures.cpp.

 void dense_dot_range_subset ( int32_t * sub_index, int32_t num, float64_t * output, float64_t * alphas, float64_t * vec, int32_t dim, float64_t b )
virtualinherited

Compute the dot product for a subset of vectors. This function makes use of dense_dot alphas[i] * sparse[i]^T * w + b

Parameters
 sub_index index for which to compute outputs num length of index output result for the given vector range alphas scalars to multiply with, may be NULL vec dense vector to compute dot product with dim length of the dense vector b bias

Reimplemented in CCombinedDotFeatures, and CHashedWDFeaturesTransposed.

Definition at line 107 of file DotFeatures.cpp.

 float64_t dense_dot_sgvec ( int32_t vec_idx1, const SGVector< float64_t > vec2 )
virtualinherited

compute dot product between vector1 and a dense vector

Parameters
 vec_idx1 index of first vector vec2 dense vector

Reimplemented in CHashedDocDotFeatures.

Definition at line 48 of file DotFeatures.cpp.

 float64_t dot ( int32_t vec_idx1, CDotFeatures * df, int32_t vec_idx2 )
virtual

compute dot product between vector1 and vector2, appointed by their indices

possible with subset

Parameters
 vec_idx1 index of first vector df DotFeatures (of same kind) to compute dot product with vec_idx2 index of second vector

Implements CDotFeatures.

Definition at line 90 of file RandomKitchenSinksDotFeatures.cpp.

 float64_t dot ( index_t vec_idx, index_t par_idx )
protectedvirtual

Method used before computing the dot product between a feature vector and a parameter vector

Parameters
 vec_idx the feature vector index par_idx the parameter vector index

Definition at line 199 of file RandomKitchenSinksDotFeatures.cpp.

 CFeatures * duplicate ( ) const
virtual

duplicate

Implements CFeatures.

Reimplemented in CRandomFourierDotFeatures.

Definition at line 188 of file RandomKitchenSinksDotFeatures.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
 other object to compare with accuracy accuracy to use for comparison (optional) tolerant allows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 656 of file SGObject.cpp.

 void free_feature_iterator ( void * iterator )
virtual

clean up iterator call this function with the iterator returned by get_first_feature

Parameters
 iterator as returned by get_first_feature

Implements CDotFeatures.

Definition at line 163 of file RandomKitchenSinksDotFeatures.cpp.

 SGMatrix< float64_t > generate_random_coefficients ( )

generate the random coefficients and return them in a matrix where each column is a parameter vector

Returns
the parameter vectors in a matrix

Definition at line 39 of file RandomKitchenSinksDotFeatures.cpp.

 virtual SGVector generate_random_parameter_vector ( )
protectedpure virtual

Generates a random parameter vector, subclasses must override this

Returns
a random parameter vector

Implemented in CRandomFourierDotFeatures.

 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
 _tag name and type information of parameter
Returns
value of the parameter identified by the input tag

Definition at line 381 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
 name name of the parameter
Returns
value of the parameter corresponding to the input name and type

Definition at line 404 of file SGObject.h.

 int32_t get_cache_size ( ) const
inherited

get cache size

Returns
cache size

Definition at line 160 of file Features.cpp.

 float64_t get_combined_feature_weight ( )
inherited

get combined feature weight

Returns
combined feature weight

Definition at line 150 of file DotFeatures.h.

 SGMatrix< float64_t > get_computed_dot_feature_matrix ( )
inherited

compute the feature matrix in feature space

Returns
computed feature matrix

Definition at line 153 of file DotFeatures.cpp.

 SGVector< float64_t > get_computed_dot_feature_vector ( int32_t num )
inherited

compute the feature vector in feature space

Returns
computed feature vector

Definition at line 174 of file DotFeatures.cpp.

 SGMatrix< float64_t > get_cov ( bool copy_data_for_speed = true )
virtualinherited

get covariance

Parameters
 copy_data_for_speed if true, the method stores explicitly the centered data matrix and the covariance is calculated by matrix product of the centered data with its transpose, this make it possible to take advantage of multithreaded matrix product, this may not be possible if the data doesn't fit into memory, in such case set this parameter to false to compute iteratively the covariance matrix without storing the centered data. [default = true]
Returns
covariance

Definition at line 298 of file DotFeatures.cpp.

 int32_t get_dim_feature_space ( ) const
virtual

obtain the dimensionality of the feature space

(not mix this up with the dimensionality of the input space, usually obtained via get_num_features())

Returns
dimensionality

Implements CDotFeatures.

Definition at line 85 of file RandomKitchenSinksDotFeatures.cpp.

 EFeatureClass get_feature_class ( ) const
virtual

get feature class

Returns
feature class DENSE

Implements CFeatures.

Definition at line 173 of file RandomKitchenSinksDotFeatures.cpp.

 bool get_feature_class_compatibility ( EFeatureClass rhs ) const
virtualinherited

Given a class in right hand side, does this class support compatible computation?

for example, is this->dot(rhs_prt) valid, where rhs_prt is the class in right hand side

Parameters
 rhs the class in right hand side
Returns
whether this class supports compatible computation

Reimplemented in CDenseSubSamplesFeatures< ST >.

Definition at line 355 of file Features.cpp.

 void * get_feature_iterator ( int32_t vector_index )
virtual

iterate over the non-zero features

call get_feature_iterator first, followed by get_next_feature and free_feature_iterator to cleanup

possible with subset

Parameters
 vector_index the index of the vector over whose components to iterate over
Returns
feature iterator (to be passed to get_next_feature)

Implements CDotFeatures.

Definition at line 150 of file RandomKitchenSinksDotFeatures.cpp.

 EFeatureType get_feature_type ( ) const
virtual

get feature type

Returns
templated feature type

Implements CFeatures.

Definition at line 168 of file RandomKitchenSinksDotFeatures.cpp.

 SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 269 of file SGObject.cpp.

 Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 311 of file SGObject.cpp.

 Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 324 of file SGObject.cpp.

 SGVector< float64_t > get_mean ( )
virtualinherited

get mean

Returns
mean returned

Definition at line 253 of file DotFeatures.cpp.

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

Definition at line 536 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_name name of the parameter
Returns
description of the parameter

Definition at line 560 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_name name of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 573 of file SGObject.cpp.

 const char * get_name ( ) const
virtual
Returns
object name

Implements CSGObject.

Definition at line 183 of file RandomKitchenSinksDotFeatures.cpp.

 bool get_next_feature ( int32_t & index, float64_t & value, void * iterator )
virtual

iterate over the non-zero features

call this function with the iterator returned by get_first_feature and call free_feature_iterator to cleanup

possible with subset

Parameters
 index is returned by reference (-1 when not available) value is returned by reference iterator as returned by get_first_feature
Returns
true if a new non-zero feature got returned

Implements CDotFeatures.

Definition at line 156 of file RandomKitchenSinksDotFeatures.cpp.

 int32_t get_nnz_features_for_vector ( int32_t num )
virtual

get number of non-zero features in vector

Parameters
 num which vector
Returns
number of non-zero features in vector

Implements CDotFeatures.

Definition at line 145 of file RandomKitchenSinksDotFeatures.cpp.

 int32_t get_num_preprocessed ( ) const
inherited

get the number of applied preprocs

Returns
number of applied preprocessors

Definition at line 103 of file Features.cpp.

 int32_t get_num_preprocessors ( ) const
inherited

get number of preprocessors

Returns
number of preprocessors

Definition at line 155 of file Features.cpp.

 int32_t get_num_vectors ( ) const
virtual

get number of feature vectors

Returns
number of feature vectors

Implements CFeatures.

Definition at line 178 of file RandomKitchenSinksDotFeatures.cpp.

 SGObservable* get_parameters_observable ( )
inherited

Get parameters observable

Returns
RxCpp observable

Definition at line 415 of file SGObject.h.

 CPreprocessor * get_preprocessor ( int32_t num ) const
inherited

get specified preprocessor

Parameters
 num index of preprocessor in list

Definition at line 93 of file Features.cpp.

 SGMatrix< float64_t > get_random_coefficients ( )

returns the random function parameters that were generated through the function p

Returns
the generated random coefficients

Definition at line 194 of file RandomKitchenSinksDotFeatures.cpp.

 CSubsetStack * get_subset_stack ( )
virtualinherited

returns subset stack

Returns
subset stack

Definition at line 334 of file Features.cpp.

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

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

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

Definition at line 304 of file SGObject.h.

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

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

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

Definition at line 315 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
 name name of the parameter
Returns
true if the parameter exists with the input name and type

Definition at line 326 of file SGObject.h.

 bool has_property ( EFeatureProperty p ) const
inherited

check if features have given property

Parameters
 p feature property
Returns
if features have given property

Definition at line 295 of file Features.cpp.

 virtual Range index_iterator ( ) const
virtualinherited

returns an iterator of indices from 0 to CFeatures::get_num_vectors

Should be used in algorithms in the following way:

for (auto idx : features->index_iterator()) { ... }

Definition at line 123 of file Features.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
 generic set to the type of the generic if returning TRUE
Returns
TRUE if a class template.

Definition at line 330 of file SGObject.cpp.

 bool is_preprocessed ( int32_t num ) const
inherited

get whether specified preprocessor was already applied

Parameters
 num index of preprocessor in list

Definition at line 149 of file Features.cpp.

 void list_feature_obj ( ) const
inherited

list feature object

Definition at line 171 of file Features.cpp.

 void list_observable_parameters ( )
inherited

Print to stdout a list of observable parameters

Definition at line 878 of file SGObject.cpp.

 void list_preprocessors ( )
inherited

print preprocessors

Definition at line 131 of file Features.cpp.

virtualinherited

Parameters

Definition at line 269 of file Features.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
 file where to load from prefix prefix for members
Returns
TRUE if done, otherwise FALSE

Definition at line 403 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
 ShogunException will be thrown if an error occurs.

Definition at line 460 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
 ShogunException will be thrown if an error occurs.

Definition at line 455 of file SGObject.cpp.

 void observe ( const ObservedValue value )
protectedinherited

Observe a parameter value and emit them to observer.

Parameters
 value Observed parameter's value

Definition at line 828 of file SGObject.cpp.

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

Definition at line 296 of file SGObject.cpp.

 float64_t post_dot ( float64_t dot_result, index_t par_idx )
protectedvirtual

subclass must override this to perform any operations on the dot result between a feature vector and a parameter vector w

Parameters
 dot_result the result of the dot operation par_idx the idx of the parameter vector
Returns
the (optionally) modified result

Reimplemented in CRandomFourierDotFeatures.

Definition at line 205 of file RandomKitchenSinksDotFeatures.cpp.

 void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 512 of file SGObject.cpp.

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

prints registered parameters out

Parameters
 prefix prefix for members

Definition at line 342 of file SGObject.cpp.

 int32_t ref ( )
inherited

increase reference counter

Returns
reference count

Definition at line 186 of file SGObject.cpp.

 int32_t ref_count ( )
inherited

display reference counter

Returns
reference count

Definition at line 193 of file SGObject.cpp.

 void register_observable_param ( const std::string & name, const SG_OBS_VALUE_TYPE type, const std::string & description )
protectedinherited

Register which params this object can emit.

Parameters
 name the param name type the param type description a user oriented description

Definition at line 871 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
 _tag name and type information of parameter value value of the parameter

Definition at line 472 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
 name name of the parameter value value of the parameter along with type information

Definition at line 485 of file SGObject.h.

 void remove_all_subsets ( )
virtualinherited

removes all subsets Calls subset_changed_post() afterwards

Reimplemented in CCombinedFeatures.

Definition at line 328 of file Features.cpp.

 void remove_subset ( )
virtualinherited

removes that last added subset from subset stack, if existing Calls subset_changed_post() afterwards

Reimplemented in CCombinedFeatures.

Definition at line 322 of file Features.cpp.

 bool reshape ( int32_t num_features, int32_t num_vectors )
virtualinherited

in case there is a feature matrix allow for reshaping

NOT IMPLEMENTED!

Parameters
 num_features new number of features num_vectors new number of vectors
Returns
if reshaping was successful

Definition at line 165 of file Features.cpp.

 void save ( CFile * writer )
virtualinherited

save features to file

Parameters
 writer File object via which data shall be saved

Definition at line 276 of file Features.cpp.

 bool save_serializable ( CSerializableFile * file, const char * prefix = "" )
virtualinherited

Save this object to file.

Parameters
 file where to save the object; will be closed during returning if PREFIX is an empty string. prefix prefix for members
Returns
TRUE if done, otherwise FALSE

Definition at line 348 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
 ShogunException will be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 470 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
 ShogunException will be thrown if an error occurs.

Definition at line 465 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
 _tag name and type information of parameter value value of the parameter

Definition at line 342 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
 name name of the parameter value value of the parameter along with type information

Definition at line 368 of file SGObject.h.

 void set_combined_feature_weight ( float64_t nw )
inherited

set combined kernel weight

Parameters
 nw new combined feature weight

Definition at line 156 of file DotFeatures.h.

 void set_generic ( )
inherited

Definition at line 73 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 78 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 83 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 88 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 93 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 98 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 103 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 108 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 113 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 118 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 123 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 128 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 133 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 138 of file SGObject.cpp.

 void set_generic ( )
inherited

Definition at line 143 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
 io io object to use

Definition at line 262 of file SGObject.cpp.

 void set_global_parallel ( Parallel * parallel )
inherited

set the parallel object

Parameters
 parallel parallel object to use

Definition at line 275 of file SGObject.cpp.

 void set_global_version ( Version * version )
inherited

set the version object

Parameters
 version version object to use

Definition at line 317 of file SGObject.cpp.

 void set_preprocessed ( int32_t num )
inherited

set applied flag for preprocessor

Parameters
 num index of preprocessor in list

Definition at line 143 of file Features.cpp.

 void set_property ( EFeatureProperty p )
inherited

set property

Parameters
 p kernel property to set

Definition at line 300 of file Features.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 226 of file SGObject.cpp.

 virtual CFeatures* shallow_subset_copy ( )
virtualinherited

Definition at line 353 of file Features.h.

 void subscribe_to_parameters ( ParameterObserverInterface * obs )
inherited

Subscribe a parameter observer to watch over params

Definition at line 811 of file SGObject.cpp.

 virtual void subset_changed_post ( )
virtualinherited

method may be overwritten to update things that depend on subset

Definition at line 310 of file Features.h.

 virtual bool support_compatible_class ( ) const
virtualinherited

does this class support compatible computation bewteen difference classes? for example, this->dot(rhs_prt), can rhs_prt be an instance of a difference class?

Returns
whether this class supports compatible computation

Reimplemented in CDenseSubSamplesFeatures< ST >.

Definition at line 340 of file Features.h.

 int32_t unref ( )
inherited

decrement reference counter and deallocate object if refcount is zero before or after decrementing it

Returns
reference count

Definition at line 200 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 337 of file SGObject.cpp.

 void unset_property ( EFeatureProperty p )
inherited

unset property

Parameters
 p kernel property to unset

Definition at line 305 of file Features.cpp.

 void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 282 of file SGObject.cpp.

## Member Data Documentation

 float64_t combined_weight
protectedinherited

feature weighting in combined dot features

Definition at line 248 of file DotFeatures.h.

 CDotFeatures* feats
protected

the dataset to work on

Definition at line 240 of file RandomKitchenSinksDotFeatures.h.

 SGIO* io
inherited

io

Definition at line 600 of file SGObject.h.

inherited

parameters wrt which we can compute gradients

Definition at line 615 of file SGObject.h.

 uint32_t m_hash
inherited

Hash of parameter values

Definition at line 618 of file SGObject.h.

 Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 612 of file SGObject.h.

 Parameter* m_parameters
inherited

parameters

Definition at line 609 of file SGObject.h.

 CSubsetStack* m_subset_stack
protectedinherited

subset used for index transformations

Definition at line 378 of file Features.h.

 int32_t num_samples
protected

the number of samples to use

Definition at line 243 of file RandomKitchenSinksDotFeatures.h.

 Parallel* parallel
inherited

parallel

Definition at line 603 of file SGObject.h.

 SGMatrix random_coeff
protected

random coefficients of the function phi, drawn from p

Definition at line 246 of file RandomKitchenSinksDotFeatures.h.

 Version* version
inherited

version

Definition at line 606 of file SGObject.h.

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

SHOGUN Machine Learning Toolbox - Documentation