SHOGUN  6.1.3
FirstOrderStochasticMinimizer Class Referenceabstract

## Detailed Description

The base class for stochastic first-order gradient-based minimizers.

This class gives the interface of these stochastic minimizers.

A stochastic minimizer is used to minimize a cost function $$f(w)$$ which can be written as a (finite) sum of differentiable functions, $$f_i(w)$$. (eg, FirstOrderStochasticCostFunction) For example,

$f(w)=\sum_i{ f_i(w) }$

Note that we call these differentiable functions $$f_i(w)$$ as sample functions.

This kind of minimizers will find optimal target variables based on gradient information wrt target variables. FirstOrderStochasticMinimizer uses a sample gradient (eg, FirstOrderStochasticCostFunction::get_gradient() ) $$\frac{\partial f_i(w) }{\partial w}$$ to find optimal target variables, where the index $$i$$ is generated by some distribution (eg, FirstOrderStochasticCostFunction::next_sample() ).

Note that FirstOrderMinimizer uses the exact gradient, (eg, FirstOrderCostFunction::get_gradient() ), $$\frac{\partial f(w) }{\partial w}$$.

For example, least sqaures cost function

$f(w)=\sum_i{ (y_i-w^T x_i)^2 }$

If we let $$f_i(w)=(y_i-w^T x_i)^2$$, $$f(w)$$ can be written as $$f(w)=\sum_i{ f_i(w) }$$. Note that $$f_i(w)$$ is a sample function for the i-th sample, $$(x_i,y_i)$$.

Definition at line 69 of file FirstOrderStochasticMinimizer.h.

Inheritance diagram for FirstOrderStochasticMinimizer:
[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

FirstOrderStochasticMinimizer ()

FirstOrderStochasticMinimizer (FirstOrderStochasticCostFunction *fun)

virtual const char * get_name () const

virtual ~FirstOrderStochasticMinimizer ()

virtual bool supports_batch_update () const

virtual float64_t minimize ()=0

virtual void set_number_passes (int32_t num_passes)

virtual void set_learning_rate (LearningRate *learning_rate)

virtual int32_t get_iteration_counter ()

virtual void set_cost_function (FirstOrderCostFunction *fun)

virtual void unset_cost_function (bool is_unref=true)

virtual void set_penalty_weight (float64_t penalty_weight)

virtual void set_penalty_type (Penalty *penalty_type)

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 ()

## Public Attributes

SGIOio

Parallelparallel

Versionversion

Parameterm_parameters

Parameterm_model_selection_parameters

uint32_t m_hash

## Protected Member Functions

virtual void do_proximal_operation (SGVector< float64_t >variable_reference)

virtual void init_minimization ()

virtual float64_t get_penalty (SGVector< float64_t > var)

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

int32_t m_num_passes

int32_t m_cur_passes

int32_t m_iter_counter

LearningRatem_learning_rate

FirstOrderCostFunctionm_fun

Penaltym_penalty_type

float64_t m_penalty_weight

## ◆ SGObservable

 inherited

Definition at line 130 of file SGObject.h.

## ◆ SGSubject

 inherited

Definition at line 127 of file SGObject.h.

## ◆ SGSubscriber

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

Definition at line 133 of file SGObject.h.

## ◆ FirstOrderStochasticMinimizer() [1/2]

 FirstOrderStochasticMinimizer ( )

Default constructor

Definition at line 73 of file FirstOrderStochasticMinimizer.h.

## ◆ FirstOrderStochasticMinimizer() [2/2]

 FirstOrderStochasticMinimizer ( FirstOrderStochasticCostFunction * fun )

Constructor

Parameters
 fun stochastic cost function

Definition at line 82 of file FirstOrderStochasticMinimizer.h.

## ◆ ~FirstOrderStochasticMinimizer()

 ~FirstOrderStochasticMinimizer ( )
virtual

Destructor

Definition at line 49 of file FirstOrderStochasticMinimizer.cpp.

## Member Function Documentation

 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.

## ◆ clone()

 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.

## ◆ clone_parameters()

 bool clone_parameters ( CSGObject * other )
protectedinherited

Definition at line 759 of file SGObject.cpp.

## ◆ deep_copy()

 CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 232 of file SGObject.cpp.

## ◆ do_proximal_operation()

 void do_proximal_operation ( SGVector< float64_t > variable_reference )
protectedvirtual

Do proximal update in place

Parameters
 variable_reference variable_reference to be updated

Definition at line 71 of file FirstOrderStochasticMinimizer.cpp.

## ◆ equals()

 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.

## ◆ get() [1/2]

 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.

## ◆ get() [2/2]

 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.

## ◆ get_global_io()

 SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 269 of file SGObject.cpp.

## ◆ get_global_parallel()

 Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 311 of file SGObject.cpp.

## ◆ get_global_version()

 Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 324 of file SGObject.cpp.

## ◆ get_iteration_counter()

 virtual int32_t get_iteration_counter ( )
virtual

How many samples/mini-batch does the minimizer use?

Returns
the number of samples/mini-batches used in optimization

Definition at line 136 of file FirstOrderStochasticMinimizer.h.

## ◆ get_modelsel_names()

 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.

## ◆ get_modsel_param_descr()

 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.

## ◆ get_modsel_param_index()

 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.

## ◆ get_name()

 virtual const char* get_name ( ) const
virtual

returns the name of the class

Returns
name FirstOrderStochasticMinimizer

Reimplemented from FirstOrderMinimizer.

Reimplemented in SMIDASMinimizer, SVRGMinimizer, SMDMinimizer, and SGDMinimizer.

Definition at line 92 of file FirstOrderStochasticMinimizer.h.

## ◆ get_parameters_observable()

 SGObservable* get_parameters_observable ( )
inherited

Get parameters observable

Returns
RxCpp observable

Definition at line 415 of file SGObject.h.

## ◆ get_penalty()

 float64_t get_penalty ( SGVector< float64_t > var )
protectedvirtualinherited

Get the penalty given target variables For L2 penalty, the target variable is $$w$$ and the value of penalty is $$\lambda \frac{w^t w}{2}$$, where $$\lambda$$ is the weight of penalty

Parameters
 var the variable used in regularization

Definition at line 69 of file FirstOrderMinimizer.cpp.

## ◆ has() [1/3]

 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.

## ◆ has() [2/3]

 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.

## ◆ has() [3/3]

 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.

## ◆ init_minimization()

 void init_minimization ( )
protectedvirtual

init the minimization process

Reimplemented in SVRGMinimizer, SMDMinimizer, SMIDASMinimizer, and SGDMinimizer.

Definition at line 87 of file FirstOrderStochasticMinimizer.cpp.

## ◆ is_generic()

 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.

## ◆ list_observable_parameters()

 void list_observable_parameters ( )
inherited

Print to stdout a list of observable parameters

Definition at line 878 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
 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.

## ◆ minimize()

 virtual float64_t minimize ( )
pure virtual

Do minimization and get the optimal value

Returns
optimal value

Implements Minimizer.

Implemented in SGDMinimizer, SMIDASMinimizer, SVRGMinimizer, and SMDMinimizer.

## ◆ observe()

 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.

## ◆ parameter_hash_changed()

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

Definition at line 296 of file SGObject.cpp.

## ◆ print_modsel_params()

 void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 512 of file SGObject.cpp.

## ◆ print_serializable()

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

prints registered parameters out

Parameters
 prefix prefix for members

Definition at line 342 of file SGObject.cpp.

## ◆ ref()

 int32_t ref ( )
inherited

increase reference counter

Returns
reference count

Definition at line 186 of file SGObject.cpp.

## ◆ ref_count()

 int32_t ref_count ( )
inherited

display reference counter

Returns
reference count

Definition at line 193 of file SGObject.cpp.

## ◆ register_observable_param()

 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.

## ◆ register_param() [1/2]

 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.

## ◆ register_param() [2/2]

 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.

## ◆ save_serializable()

 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.

## ◆ save_serializable_post()

 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.

## ◆ save_serializable_pre()

 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.

## ◆ set() [1/2]

 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.

## ◆ set() [2/2]

 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.

## ◆ set_cost_function()

 void set_cost_function ( FirstOrderCostFunction * fun )
virtualinherited

Set cost function used in the minimizer

Parameters
 fun the cost function

Definition at line 42 of file FirstOrderMinimizer.cpp.

## ◆ set_generic() [1/16]

 void set_generic ( )
inherited

Definition at line 73 of file SGObject.cpp.

## ◆ set_generic() [2/16]

 void set_generic ( )
inherited

Definition at line 78 of file SGObject.cpp.

## ◆ set_generic() [3/16]

 void set_generic ( )
inherited

Definition at line 83 of file SGObject.cpp.

## ◆ set_generic() [4/16]

 void set_generic ( )
inherited

Definition at line 88 of file SGObject.cpp.

## ◆ set_generic() [5/16]

 void set_generic ( )
inherited

Definition at line 93 of file SGObject.cpp.

## ◆ set_generic() [6/16]

 void set_generic ( )
inherited

Definition at line 98 of file SGObject.cpp.

## ◆ set_generic() [7/16]

 void set_generic ( )
inherited

Definition at line 103 of file SGObject.cpp.

## ◆ set_generic() [8/16]

 void set_generic ( )
inherited

Definition at line 108 of file SGObject.cpp.

## ◆ set_generic() [9/16]

 void set_generic ( )
inherited

Definition at line 113 of file SGObject.cpp.

## ◆ set_generic() [10/16]

 void set_generic ( )
inherited

Definition at line 118 of file SGObject.cpp.

## ◆ set_generic() [11/16]

 void set_generic ( )
inherited

Definition at line 123 of file SGObject.cpp.

## ◆ set_generic() [12/16]

 void set_generic ( )
inherited

Definition at line 128 of file SGObject.cpp.

## ◆ set_generic() [13/16]

 void set_generic ( )
inherited

Definition at line 133 of file SGObject.cpp.

## ◆ set_generic() [14/16]

 void set_generic ( )
inherited

Definition at line 138 of file SGObject.cpp.

## ◆ set_generic() [15/16]

 void set_generic ( )
inherited

Definition at line 143 of file SGObject.cpp.

## ◆ set_generic() [16/16]

 void set_generic ( )
inherited

set generic type to T

## ◆ set_global_io()

 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.

## ◆ set_global_parallel()

 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.

## ◆ set_global_version()

 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.

virtual

Parameters

Definition at line 38 of file FirstOrderStochasticMinimizer.cpp.

## ◆ set_learning_rate()

 void set_learning_rate ( LearningRate * learning_rate )
virtual

Set the learning rate of a minimizer

Parameters
 learning_rate learn rate or step size

Definition at line 61 of file FirstOrderStochasticMinimizer.cpp.

## ◆ set_number_passes()

 void set_number_passes ( int32_t num_passes )
virtual

Set the number of times to go through all data points (samples) For example, num_passes=1 means go through all data points once.

Recall that a stochastic cost function $$f(w)$$ can be written as $$\sum_i{ f_i(w) }$$, where $$f_i(w)$$ is the differentiable function for the i-th sample.

Parameters
 num_passes the number of times

Definition at line 55 of file FirstOrderStochasticMinimizer.cpp.

## ◆ set_penalty_type()

 void set_penalty_type ( Penalty * penalty_type )
virtualinherited

Set the type of penalty For example, L2 penalty

Parameters
 penalty_type the type of penalty. If NULL is given, regularization is not enabled.

Definition at line 53 of file FirstOrderMinimizer.cpp.

## ◆ set_penalty_weight()

 void set_penalty_weight ( float64_t penalty_weight )
virtualinherited

Set the weight of penalty

Parameters
 penalty_weight the weight of penalty, which is positive

Definition at line 63 of file FirstOrderMinimizer.cpp.

## ◆ shallow_copy()

 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.

## ◆ subscribe_to_parameters()

 void subscribe_to_parameters ( ParameterObserverInterface * obs )
inherited

Subscribe a parameter observer to watch over params

Definition at line 811 of file SGObject.cpp.

## ◆ supports_batch_update()

 virtual bool supports_batch_update ( ) const
virtual

Does minimizer support batch update

Returns
whether minimizer supports batch update

Implements FirstOrderMinimizer.

Definition at line 102 of file FirstOrderStochasticMinimizer.h.

## ◆ unref()

 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.

## ◆ unset_cost_function()

 virtual void unset_cost_function ( bool is_unref = true )
virtualinherited

Unset cost function used in the minimizer

Definition at line 94 of file FirstOrderMinimizer.h.

## ◆ unset_generic()

 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 update_gradient ( SGVector< float64_t > gradient, SGVector< float64_t > var )
protectedvirtualinherited

Add gradient of the penalty wrt target variables to unpenalized gradient For least sqaure with L2 penalty,

$L2f(w)=f(w) + L2(w)$

where $$f(w)=\sum_i{(y_i-w^T x_i)^2}$$ is the least sqaure cost function and $$L2(w)=\lambda \frac{w^t w}{2}$$ is the L2 penalty

Target variables is $$w$$ Unpenalized gradient is $$\frac{\partial f(w) }{\partial w}$$ Gradient of the penalty wrt target variables is $$\frac{\partial L2(w) }{\partial w}$$

Parameters

Definition at line 81 of file FirstOrderMinimizer.cpp.

## ◆ update_parameter_hash()

 void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 282 of file SGObject.cpp.

## ◆ io

 SGIO* io
inherited

io

Definition at line 600 of file SGObject.h.

## ◆ m_cur_passes

 int32_t m_cur_passes
protected

current iteration to go through data

Definition at line 156 of file FirstOrderStochasticMinimizer.h.

## ◆ m_fun

 FirstOrderCostFunction* m_fun
protectedinherited

Cost function

Definition at line 146 of file FirstOrderMinimizer.h.

inherited

parameters wrt which we can compute gradients

Definition at line 615 of file SGObject.h.

protected

Definition at line 150 of file FirstOrderStochasticMinimizer.h.

## ◆ m_hash

 uint32_t m_hash
inherited

Hash of parameter values

Definition at line 618 of file SGObject.h.

## ◆ m_iter_counter

 int32_t m_iter_counter
protected

number of used samples/mini-batches

Definition at line 159 of file FirstOrderStochasticMinimizer.h.

## ◆ m_learning_rate

 LearningRate* m_learning_rate
protected

learning_rate object

Definition at line 162 of file FirstOrderStochasticMinimizer.h.

## ◆ m_model_selection_parameters

 Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 612 of file SGObject.h.

## ◆ m_num_passes

 int32_t m_num_passes
protected

iteration to go through data

Definition at line 153 of file FirstOrderStochasticMinimizer.h.

## ◆ m_parameters

 Parameter* m_parameters
inherited

parameters

Definition at line 609 of file SGObject.h.

## ◆ m_penalty_type

 Penalty* m_penalty_type
protectedinherited

the type of penalty

Definition at line 149 of file FirstOrderMinimizer.h.

## ◆ m_penalty_weight

 float64_t m_penalty_weight
protectedinherited

the weight of penalty

Definition at line 152 of file FirstOrderMinimizer.h.

## ◆ parallel

 Parallel* parallel
inherited

parallel

Definition at line 603 of file SGObject.h.

## ◆ version

 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