Inheritance diagram for xgboost::LearnerConfiguration:

Public Member Functions
	LearnerConfiguration (std::vector< std::shared_ptr< DMatrix > > cache)

void	Configure () override
	Configure Learner based on set parameters.

void	CheckModelInitialized () const

void	LoadConfig (Json const &in) override
	Load configuration from JSON object.

void	SaveConfig (Json *p_out) const override
	Save configuration to JSON object.

void	SetParam (const std::string &key, const std::string &value) override
	Set parameter for booster.

void	SetParams (std::vector< std::pair< std::string, std::string > > const &args) override
	Set multiple parameters at once.

uint32_t	GetNumFeature () const override
	Get the number of features of the booster.

void	SetAttr (const std::string &key, const std::string &value) override
	Set additional attribute to the Booster.

bool	GetAttr (const std::string &key, std::string *out) const override
	Get attribute from the booster. The property will be saved along the booster.

bool	DelAttr (const std::string &key) override
	Delete an attribute from the booster.

void	SetFeatureNames (std::vector< std::string > const &fn) override
	Set the feature names for current booster.

void	GetFeatureNames (std::vector< std::string > *fn) const override
	Get the feature names for current booster.

void	SetFeatureTypes (std::vector< std::string > const &ft) override
	Set the feature types for current booster.

void	GetFeatureTypes (std::vector< std::string > *p_ft) const override
	Get the feature types for current booster.

std::vector< std::string >	GetAttrNames () const override
	Get a vector of attribute names from the booster.

const std::map< std::string, std::string > &	GetConfigurationArguments () const override
	Get configuration arguments currently stored by the learner.

Context const *	Ctx () const override
	Return the context object of this Booster.

Public Member Functions inherited from xgboost::Learner
	~Learner () override
	virtual destructor

virtual void	UpdateOneIter (int iter, std::shared_ptr< DMatrix > train)=0
	update the model for one iteration With the specified objective function.

virtual void	BoostOneIter (int iter, std::shared_ptr< DMatrix > train, HostDeviceVector< GradientPair > *in_gpair)=0
	Do customized gradient boosting with in_gpair. in_gair can be mutated after this call.

virtual std::string	EvalOneIter (int iter, const std::vector< std::shared_ptr< DMatrix > > &data_sets, const std::vector< std::string > &data_names)=0
	evaluate the model for specific iteration using the configured metrics.

virtual void	Predict (std::shared_ptr< DMatrix > data, bool output_margin, HostDeviceVector< bst_float > *out_preds, bst_layer_t layer_begin, bst_layer_t layer_end, bool training=false, bool pred_leaf=false, bool pred_contribs=false, bool approx_contribs=false, bool pred_interactions=false)=0
	get prediction given the model.

virtual void	InplacePredict (std::shared_ptr< DMatrix > p_m, PredictionType type, float missing, HostDeviceVector< float > **out_preds, bst_layer_t layer_begin, bst_layer_t layer_end)=0
	Inplace prediction.

virtual void	CalcFeatureScore (std::string const &importance_type, common::Span< int32_t const > trees, std::vector< bst_feature_t > features, std::vector< float > scores)=0
	Calculate feature score. See doc in C API for outputs.

virtual int32_t	BoostedRounds () const =0

virtual std::uint32_t	Groups () const =0
	Get the number of output groups from the model.

void	LoadModel (Json const &in) override=0
	load the model from a JSON object

void	SaveModel (Json *out) const override=0
	saves the model config to a JSON object

virtual void	LoadModel (dmlc::Stream *fi)=0

virtual void	SaveModel (dmlc::Stream *fo) const =0

virtual Learner *	Slice (bst_layer_t begin, bst_layer_t end, bst_layer_t step, bool *out_of_bound)=0
	Slice the model.

virtual std::vector< std::string >	DumpModel (const FeatureMap &fmap, bool with_stats, std::string format)=0
	dump the model in the requested format

virtual XGBAPIThreadLocalEntry &	GetThreadLocal () const =0

Public Member Functions inherited from dmlc::Serializable
virtual	~Serializable ()
	virtual destructor

virtual void	Load (Stream *fi)=0
	load the model from a stream

virtual void	Save (Stream *fo) const =0
	saves the model to a stream

Protected Member Functions
void	ConfigureModelParamWithoutBaseScore ()

void	InitBaseScore (DMatrix const *p_fmat)
	Calculate the `base_score` based on input data.

Protected Attributes
std::atomic< bool >	need_configuration_

std::map< std::string, std::string >	cfg_

std::map< std::string, std::string >	attributes_

std::vector< std::string >	feature_names_

std::vector< std::string >	feature_types_

common::Monitor	monitor_

LearnerModelParamLegacy	mparam_

LearnerModelParam	learner_model_param_

LearnerTrainParam	tparam_

PredictionContainer	prediction_container_

std::vector< std::string >	metric_names_

Protected Attributes inherited from xgboost::Learner
std::unique_ptr< ObjFunction >	obj_
	objective function

std::unique_ptr< GradientBooster >	gbm_
	The gradient booster used by the model.

std::vector< std::unique_ptr< Metric > >	metrics_
	The evaluation metrics used to evaluate the model.

Context	ctx_
	Training parameter.

Static Protected Attributes
static std::string const	kEvalMetric {"eval_metric"}

Additional Inherited Members
Static Public Member Functions inherited from xgboost::Learner
static Learner *	Create (const std::vector< std::shared_ptr< DMatrix > > &cache_data)
	Create a new instance of learner.

Member Function Documentation

◆ Configure()

void xgboost::LearnerConfiguration::Configure ( )

inlineoverridevirtual

Configure Learner based on set parameters.

Implements xgboost::Learner.

◆ Ctx()

Context const * xgboost::LearnerConfiguration::Ctx ( ) const

inlineoverridevirtual

Return the context object of this Booster.

Implements xgboost::Learner.

◆ DelAttr()

bool xgboost::LearnerConfiguration::DelAttr ( const std::string & key )

inlineoverridevirtual

Delete an attribute from the booster.

Parameters

key	The key of the attribute.

Returns: Whether the key was found among booster's attributes.

Implements xgboost::Learner.

◆ GetAttr()

bool xgboost::LearnerConfiguration::GetAttr	(	const std::string &	key,
		std::string *	out
	)		const

inlineoverridevirtual

Get attribute from the booster. The property will be saved along the booster.

Parameters

key	The key of the attribute.
out	The output value.

Returns: Whether the key exists among booster's attributes.

Implements xgboost::Learner.

◆ GetAttrNames()

std::vector< std::string > xgboost::LearnerConfiguration::GetAttrNames ( ) const

inlineoverridevirtual

Get a vector of attribute names from the booster.

Returns: vector of attribute name strings.

Implements xgboost::Learner.

◆ GetConfigurationArguments()

const std::map< std::string, std::string > & xgboost::LearnerConfiguration::GetConfigurationArguments ( ) const

inlineoverridevirtual

Get configuration arguments currently stored by the learner.

Returns: Key-value pairs representing configuration arguments

Implements xgboost::Learner.

Reimplemented in xgboost::LearnerImpl.

◆ GetFeatureNames()

void xgboost::LearnerConfiguration::GetFeatureNames ( std::vector< std::string > * fn ) const

inlineoverridevirtual

Get the feature names for current booster.

Parameters

fn	Output feature names

Implements xgboost::Learner.

◆ GetFeatureTypes()

void xgboost::LearnerConfiguration::GetFeatureTypes ( std::vector< std::string > * ft ) const

inlineoverridevirtual

Get the feature types for current booster.

Parameters

fn	Output feature types

Implements xgboost::Learner.

◆ GetNumFeature()

uint32_t xgboost::LearnerConfiguration::GetNumFeature ( ) const

inlineoverridevirtual

Get the number of features of the booster.

Returns: number of features

Implements xgboost::Learner.

◆ InitBaseScore()

void xgboost::LearnerConfiguration::InitBaseScore ( DMatrix const * p_fmat )

inlineprotected

Calculate the base_score based on input data.

Parameters

p_fmat The training DMatrix used to estimate the base score.

◆ LoadConfig()

void xgboost::LearnerConfiguration::LoadConfig ( Json const & in )

inlineoverridevirtual

Load configuration from JSON object.

Parameters

in	JSON object containing the configuration

Implements xgboost::Configurable.

◆ SaveConfig()

void xgboost::LearnerConfiguration::SaveConfig ( Json * out ) const

inlineoverridevirtual

Save configuration to JSON object.

Parameters

out	pointer to output JSON object

Implements xgboost::Configurable.

◆ SetAttr()

void xgboost::LearnerConfiguration::SetAttr	(	const std::string &	key,
		const std::string &	value
	)

inlineoverridevirtual

Set additional attribute to the Booster.

The property will be saved along the booster.

Parameters

key	The key of the property.
value	The value of the property.

Implements xgboost::Learner.

◆ SetFeatureNames()

void xgboost::LearnerConfiguration::SetFeatureNames ( std::vector< std::string > const & fn )

inlineoverridevirtual

Set the feature names for current booster.

Parameters

fn	Input feature names

Implements xgboost::Learner.

◆ SetFeatureTypes()

void xgboost::LearnerConfiguration::SetFeatureTypes ( std::vector< std::string > const & ft )

inlineoverridevirtual

Set the feature types for current booster.

Parameters

ft	Input feature types.

Implements xgboost::Learner.

◆ SetParam()

void xgboost::LearnerConfiguration::SetParam	(	const std::string &	key,
		const std::string &	value
	)

inlineoverridevirtual

Set parameter for booster.

The property will NOT be saved along with booster

Parameters

key	The key of parameter
value	The value of parameter

Implements xgboost::Learner.

◆ SetParams()

void xgboost::LearnerConfiguration::SetParams ( std::vector< std::pair< std::string, std::string > > const & args )

inlineoverridevirtual

Set multiple parameters at once.

Parameters

args	parameters.

Implements xgboost::Learner.

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

External/xgboost/src/learner.cc

Public Member Functions

Protected Member Functions

Protected Attributes

Static Protected Attributes

Additional Inherited Members

Member Function Documentation

◆ Configure()

◆ Ctx()

◆ DelAttr()

◆ GetAttr()

◆ GetAttrNames()

◆ GetConfigurationArguments()

◆ GetFeatureNames()

◆ GetFeatureTypes()

◆ GetNumFeature()

◆ InitBaseScore()

◆ LoadConfig()

◆ SaveConfig()

◆ SetAttr()

◆ SetFeatureNames()

◆ SetFeatureTypes()

◆ SetParam()

◆ SetParams()