BayesNet 1.0.7.
Bayesian Network and basic classifiers Library.
Loading...
Searching...
No Matches
Public Member Functions | Protected Member Functions | List of all members
bayesnet::XSpode Class Reference
Inheritance diagram for bayesnet::XSpode:
Inheritance graph
[legend]
Collaboration diagram for bayesnet::XSpode:
Collaboration graph
[legend]

Public Member Functions

 XSpode (int spIndex)
 
std::vector< double > predict_proba (const std::vector< int > &instance) const
 
std::vector< std::vector< double > > predict_proba (std::vector< std::vector< int > > &X) override
 
int predict (const std::vector< int > &instance) const
 
void normalize (std::vector< double > &v) const
 
std::string to_string () const
 
int getNFeatures () const
 
int getNumberOfNodes () const override
 
int getNumberOfEdges () const override
 
int getNumberOfStates () const override
 
int getClassNumStates () const override
 
std::vector< int > & getStates ()
 
std::vector< std::string > graph (const std::string &title) const override
 
void fitx (torch::Tensor &X, torch::Tensor &y, torch::Tensor &weights_, const Smoothing_t smoothing)
 
void setHyperparameters (const nlohmann::json &hyperparameters_) override
 
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
 
float score (torch::Tensor &X, torch::Tensor &y) override
 
float score (std::vector< std::vector< int > > &X, std::vector< int > &y) 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, const Smoothing_t smoothing) 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, const Smoothing_t smoothing) 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 Smoothing_t smoothing) 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, const Smoothing_t smoothing) override
 
void addNodes ()
 
status_t getStatus () const override
 
std::string getVersion () override
 
std::vector< std::string > show () const override
 
std::vector< std::string > topological_order () override
 
std::vector< std::string > getNotes () const override
 
std::string dump_cpt () const override
 
- Public Member Functions inherited from bayesnet::BaseClassifier
std::vector< std::string > & getValidHyperparameters ()
 

Protected Member Functions

void buildModel (const torch::Tensor &weights) override
 
void trainModel (const torch::Tensor &weights, const bayesnet::Smoothing_t smoothing) override
 
- Protected Member Functions inherited from bayesnet::Classifier
void checkFitParameters ()
 
void buildDataset (torch::Tensor &y)
 
- Protected Member Functions inherited from bayesnet::BaseClassifier

Additional Inherited Members

- 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
 
const std::string CLASSIFIER_NOT_FITTED = "Classifier has not been fitted"
 
- Protected Attributes inherited from bayesnet::BaseClassifier
std::vector< std::string > validHyperparameters
 
std::vector< std::string > notes
 
status_t status = NORMAL
 

Detailed Description

Definition at line 17 of file XSPODE.h.

Constructor & Destructor Documentation

◆ XSpode()

bayesnet::XSpode::XSpode ( int spIndex)
explicit

Definition at line 20 of file XSPODE.cc.

Member Function Documentation

◆ buildModel()

void bayesnet::XSpode::buildModel ( const torch::Tensor & weights)
overrideprotectedvirtual

Implements bayesnet::Classifier.

Definition at line 55 of file XSPODE.cc.

◆ fitx()

void bayesnet::XSpode::fitx ( torch::Tensor & X,
torch::Tensor & y,
torch::Tensor & weights_,
const Smoothing_t smoothing )

Definition at line 38 of file XSPODE.cc.

◆ getClassNumStates()

int bayesnet::XSpode::getClassNumStates ( ) const
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 385 of file XSPODE.cc.

◆ getNFeatures()

int bayesnet::XSpode::getNFeatures ( ) const

Definition at line 386 of file XSPODE.cc.

◆ getNumberOfEdges()

int bayesnet::XSpode::getNumberOfEdges ( ) const
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 391 of file XSPODE.cc.

◆ getNumberOfNodes()

int bayesnet::XSpode::getNumberOfNodes ( ) const
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 384 of file XSPODE.cc.

◆ getNumberOfStates()

int bayesnet::XSpode::getNumberOfStates ( ) const
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 387 of file XSPODE.cc.

◆ graph()

std::vector< std::string > bayesnet::XSpode::graph ( const std::string & title) const
inlineoverridevirtual

Implements bayesnet::BaseClassifier.

Definition at line 31 of file XSPODE.h.

◆ normalize()

void bayesnet::XSpode::normalize ( std::vector< double > & v) const

Definition at line 321 of file XSPODE.cc.

◆ predict() [1/3]

int bayesnet::XSpode::predict ( const std::vector< int > & instance) const

Definition at line 399 of file XSPODE.cc.

◆ predict() [2/3]

std::vector< int > bayesnet::XSpode::predict ( std::vector< std::vector< int > > & X)
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 404 of file XSPODE.cc.

◆ predict() [3/3]

torch::Tensor bayesnet::XSpode::predict ( torch::Tensor & X)
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 416 of file XSPODE.cc.

◆ predict_proba() [1/3]

std::vector< double > bayesnet::XSpode::predict_proba ( const std::vector< int > & instance) const

Definition at line 245 of file XSPODE.cc.

◆ predict_proba() [2/3]

std::vector< std::vector< double > > bayesnet::XSpode::predict_proba ( std::vector< std::vector< int > > & X)
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 278 of file XSPODE.cc.

◆ predict_proba() [3/3]

torch::Tensor bayesnet::XSpode::predict_proba ( torch::Tensor & X)
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 422 of file XSPODE.cc.

◆ score() [1/2]

float bayesnet::XSpode::score ( std::vector< std::vector< int > > & X,
std::vector< int > & y )
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 439 of file XSPODE.cc.

◆ score() [2/2]

float bayesnet::XSpode::score ( torch::Tensor & X,
torch::Tensor & y )
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 434 of file XSPODE.cc.

◆ setHyperparameters()

void bayesnet::XSpode::setHyperparameters ( const nlohmann::json & hyperparameters_)
overridevirtual

Reimplemented from bayesnet::Classifier.

Definition at line 28 of file XSPODE.cc.

◆ to_string()

std::string bayesnet::XSpode::to_string ( ) const

Definition at line 338 of file XSPODE.cc.

◆ trainModel()

void bayesnet::XSpode::trainModel ( const torch::Tensor & weights,
const bayesnet::Smoothing_t smoothing )
overrideprotectedvirtual

Reimplemented from bayesnet::Classifier.

Definition at line 105 of file XSPODE.cc.

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