Inheritance diagram for bayesnet::Boost:

[legend]

Collaboration diagram for bayesnet::Boost:

[legend]

Public Member Functions
	Boost (bool predict_voting=false)

void	setHyperparameters (const nlohmann::json &hyperparameters_) override

Public Member Functions inherited from bayesnet::Ensemble
	Ensemble (bool predict_voting=true)

torch::Tensor	predict (torch::Tensor &X) override

std::vector< int >	predict (std::vector< std::vector< int > > &X) override

torch::Tensor	predict_proba (torch::Tensor &X) override

std::vector< std::vector< double > >	predict_proba (std::vector< std::vector< int > > &X) override

float	score (torch::Tensor &X, torch::Tensor &y) override

float	score (std::vector< std::vector< int > > &X, std::vector< int > &y) override

int	getNumberOfNodes () const override

int	getNumberOfEdges () const override

int	getNumberOfStates () const override

std::vector< std::string >	show () const override

std::vector< std::string >	graph (const std::string &title) const override

std::vector< std::string >	topological_order () override

std::string	dump_cpt () const override

Public Member Functions inherited from bayesnet::Classifier
	Classifier (Network model)

Classifier &	fit (std::vector< std::vector< int > > &X, std::vector< int > &y, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states) override

Classifier &	fit (torch::Tensor &X, torch::Tensor &y, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states) override

Classifier &	fit (torch::Tensor &dataset, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states) override

Classifier &	fit (torch::Tensor &dataset, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states, const torch::Tensor &weights) override

void	addNodes ()

int	getClassNumStates () const override

status_t	getStatus () const override

std::string	getVersion () override

std::vector< std::string >	getNotes () const override

void	setHyperparameters (const nlohmann::json &hyperparameters) override

Public Member Functions inherited from bayesnet::BaseClassifier
std::vector< std::string > &	getValidHyperparameters ()

Protected Member Functions
std::vector< int >	featureSelection (torch::Tensor &weights_)

void	buildModel (const torch::Tensor &weights) override

std::tuple< torch::Tensor &, double, bool >	update_weights (torch::Tensor &ytrain, torch::Tensor &ypred, torch::Tensor &weights)

std::tuple< torch::Tensor &, double, bool >	update_weights_block (int k, torch::Tensor &ytrain, torch::Tensor &weights)

Protected Member Functions inherited from bayesnet::Ensemble
torch::Tensor	predict_average_voting (torch::Tensor &X)

std::vector< std::vector< double > >	predict_average_voting (std::vector< std::vector< int > > &X)

torch::Tensor	predict_average_proba (torch::Tensor &X)

std::vector< std::vector< double > >	predict_average_proba (std::vector< std::vector< int > > &X)

torch::Tensor	compute_arg_max (torch::Tensor &X)

std::vector< int >	compute_arg_max (std::vector< std::vector< double > > &X)

torch::Tensor	voting (torch::Tensor &votes)

void	trainModel (const torch::Tensor &weights) override

Protected Member Functions inherited from bayesnet::Classifier
void	checkFitParameters ()

void	buildDataset (torch::Tensor &y)

Protected Attributes
torch::Tensor	X_train

torch::Tensor	y_train

torch::Tensor	X_test

torch::Tensor	y_test

bool	bisection = true

int	maxTolerance = 3

std::string	order_algorithm

bool	convergence = true

bool	convergence_best = false

bool	selectFeatures = false

std::string	select_features_algorithm = Orders.DESC

FeatureSelect *	featureSelector = nullptr

double	threshold = -1

bool	block_update = false

Protected Attributes inherited from bayesnet::Ensemble
unsigned	n_models

std::vector< std::unique_ptr< Classifier > >	models

std::vector< double >	significanceModels

bool	predict_voting

Protected Attributes inherited from bayesnet::Classifier
bool	fitted

unsigned int	m

unsigned int	n

Network	model

Metrics	metrics

std::vector< std::string >	features

std::string	className

std::map< std::string, std::vector< int > >	states

torch::Tensor	dataset

status_t	status = NORMAL

std::vector< std::string >	notes

Protected Attributes inherited from bayesnet::BaseClassifier
std::vector< std::string >	validHyperparameters

Detailed Description

Definition at line 27 of file Boost.h.

Constructor & Destructor Documentation

◆ Boost()

bayesnet::Boost::Boost ( bool predict_voting = false )

explicit

Definition at line 13 of file Boost.cc.

Member Function Documentation

◆ buildModel()

void bayesnet::Boost::buildModel ( const torch::Tensor & weights )

overrideprotectedvirtual

Implements bayesnet::Classifier.

Definition at line 71 of file Boost.cc.

◆ featureSelection()

std::vector< int > bayesnet::Boost::featureSelection ( torch::Tensor & weights_ )

protected

Definition at line 102 of file Boost.cc.

◆ setHyperparameters()

void bayesnet::Boost::setHyperparameters ( const nlohmann::json & hyperparameters_ )

overridevirtual

Implements bayesnet::BaseClassifier.

Definition at line 18 of file Boost.cc.

◆ update_weights()

std::tuple< torch::Tensor &, double, bool > bayesnet::Boost::update_weights	(	torch::Tensor &	ytrain,
		torch::Tensor &	ypred,
		torch::Tensor &	weights )

protected

Definition at line 123 of file Boost.cc.

◆ update_weights_block()

std::tuple< torch::Tensor &, double, bool > bayesnet::Boost::update_weights_block	(	int	k,
		torch::Tensor &	ytrain,
		torch::Tensor &	weights )

protected

Definition at line 150 of file Boost.cc.

Member Data Documentation

◆ bisection

bool bayesnet::Boost::bisection = true

protected

Definition at line 39 of file Boost.h.

◆ block_update

bool bayesnet::Boost::block_update = false

protected

Definition at line 48 of file Boost.h.

◆ convergence

bool bayesnet::Boost::convergence = true

protected

Definition at line 42 of file Boost.h.

◆ convergence_best

bool bayesnet::Boost::convergence_best = false

protected

Definition at line 43 of file Boost.h.

◆ featureSelector

FeatureSelect* bayesnet::Boost::featureSelector = nullptr

protected

Definition at line 46 of file Boost.h.

◆ maxTolerance

int bayesnet::Boost::maxTolerance = 3

protected

Definition at line 40 of file Boost.h.

◆ order_algorithm

std::string bayesnet::Boost::order_algorithm

protected

Definition at line 41 of file Boost.h.

◆ select_features_algorithm

std::string bayesnet::Boost::select_features_algorithm = Orders.DESC

protected

Definition at line 45 of file Boost.h.

◆ selectFeatures

bool bayesnet::Boost::selectFeatures = false

protected

Definition at line 44 of file Boost.h.

◆ threshold

double bayesnet::Boost::threshold = -1

protected

Definition at line 47 of file Boost.h.

◆ X_test

torch::Tensor bayesnet::Boost::X_test

protected

Definition at line 37 of file Boost.h.

◆ X_train

torch::Tensor bayesnet::Boost::X_train

protected

Definition at line 37 of file Boost.h.

◆ y_test

torch::Tensor bayesnet::Boost::y_test

protected

Definition at line 37 of file Boost.h.

◆ y_train

torch::Tensor bayesnet::Boost::y_train

protected

Definition at line 37 of file Boost.h.

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

/Users/rmontanana/Code/BayesNet/bayesnet/ensembles/Boost.h
/Users/rmontanana/Code/BayesNet/bayesnet/ensembles/Boost.cc

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ Boost()

Member Function Documentation

◆ buildModel()

◆ featureSelection()

◆ setHyperparameters()

◆ update_weights()

◆ update_weights_block()

Member Data Documentation

◆ bisection

◆ block_update

◆ convergence

◆ convergence_best

◆ featureSelector

◆ maxTolerance

◆ order_algorithm

◆ select_features_algorithm

◆ selectFeatures

◆ threshold

◆ X_test

◆ X_train

◆ y_test

◆ y_train