SVM (Support Vector Machines) classification of a dataset. More...

#include <pcl/ml/svm_wrapper.h>

Inheritance diagram for pcl::SVMClassify:

Collaboration diagram for pcl::SVMClassify:

Public Member Functions
	SVMClassify ()
	Constructor. More...

	~SVMClassify ()
	Destructor. More...

void	setInputTrainingSet (std::vector< SVMData > training_set)
	It adds/store the training set with labelled data. More...

std::vector< SVMData >	getInputTrainingSet ()
	Return the current training set. More...

void	resetTrainingSet ()
	Reset the training set. More...

bool	loadClassifierModel (const char *filename)
	Read in a classifier model (in svmlight format). More...

void	getClassificationResult (std::vector< std::vector< double >> &out)
	Get the result of the classification. More...

void	saveClassificationResult (const char *filename)
	Save the classification result in an extern file. More...

void	setClassifierModel (SVMModel model)
	Set the classifier model. More...

bool	loadClassProblem (const char *filename)
	Read in a raw classification problem (in svmlight format). More...

bool	loadNormClassProblem (const char *filename)
	Read in a normalized classification problem (in svmlight format). More...

void	setProbabilityEstimates (bool set)
	Set whether the classification has to be done with the probability estimate. More...

bool	classificationTest ()
	Start the classification on labelled input dataset. More...

bool	classification ()
	Start the classification on un-labelled input dataset. More...

std::vector< double >	classification (SVMData in)
	Start the classification on a single set. More...

bool	saveClassProblem (const char *filename)
	Save the raw classification problem in a file (in svmlight format). More...

bool	saveNormClassProblem (const char *filename)
	Save the normalized classification problem in a file (in svmlight format). More...

Public Member Functions inherited from pcl::SVM
	SVM ()
	Constructor. More...

	~SVM ()
	Destructor. More...

void	getLabel (std::vector< int > &labels)
	Return the labels order from the classifier model. More...

void	saveClassifierModel (const char *filename)
	Save the classifier model in an extern file (in svmlight format). More...

Protected Member Functions
void	scaleProblem (svm_problem &input, svm_scaling scaling)
	It scales the input dataset using the model information. More...

Protected Member Functions inherited from pcl::SVM
char *	readline (FILE *input)
	To read a line from the input file. More...

void	exitInputError (int line_num)
	Outputs an error in file reading. More...

const std::string &	getClassName () const
	Get a string representation of the name of this class. More...

void	adaptInputToLibSVM (std::vector< SVMData > training_set, svm_problem &prob)
	Convert the input format (vector of SVMData) into a readable format for libSVM. More...

void	adaptLibSVMToInput (std::vector< SVMData > &training_set, svm_problem prob) const
	Convert the libSVM format (svm_problem) into a easier output format. More...

bool	loadProblem (const char *filename, svm_problem &prob)
	Load a problem from an extern file. More...

bool	saveProblem (const char *filename, bool labelled)
	Save the raw problem in an extern file. More...

bool	saveProblemNorm (const char *filename, svm_problem prob_, bool labelled)
	Save the problem (with normalized values) in an extern file. More...

Protected Attributes
bool	model_extern_copied_

bool	predict_probability_ {false}

std::vector< std::vector< double > >	prediction_

std::string	class_name_

bool	labelled_training_set_

char *	line_

int	max_line_len_

SVMModel	model_

SVMParam	param_

svm_problem	prob_

svm_scaling	scaling_

std::vector< SVMData >	training_set_

Protected Attributes inherited from pcl::SVM
std::vector< SVMData >	training_set_

svm_problem	prob_

SVMModel	model_

svm_scaling	scaling_

SVMParam	param_

std::string	class_name_

char *	line_ {nullptr}

int	max_line_len_ {10000}

bool	labelled_training_set_

Additional Inherited Members
Static Protected Member Functions inherited from pcl::SVM
static void	printNull (const char *)
	Set for output printings during classification. More...

Detailed Description

SVM (Support Vector Machines) classification of a dataset.

It can be used both for testing a classifier model and for classify of new data.

Definition at line 378 of file svm_wrapper.h.

Constructor & Destructor Documentation

◆ SVMClassify()

pcl::SVMClassify::SVMClassify ( )

inline

Constructor.

Definition at line 401 of file svm_wrapper.h.

References class_name_.

◆ ~SVMClassify()

pcl::SVMClassify::~SVMClassify ( )

inline

Destructor.

Definition at line 404 of file svm_wrapper.h.

References svm_model::l, model_, and model_extern_copied_.

Member Function Documentation

◆ classification() [1/2]

bool pcl::SVMClassify::classification ( )

Start the classification on un-labelled input dataset.

To get the classification result, use getClassificationResult().

Returns: false if fails

◆ classification() [2/2]

std::vector<double> pcl::SVMClassify::classification ( SVMData in )

Start the classification on a single set.

◆ classificationTest()

bool pcl::SVMClassify::classificationTest ( )

Start the classification on labelled input dataset.

It returns the accuracy percentage. To get the classification result, use getClassificationResult().

Returns: false if fails

◆ getClassificationResult()

void pcl::SVMClassify::getClassificationResult ( std::vector< std::vector< double >> & out )

inline

Get the result of the classification.

Definition at line 450 of file svm_wrapper.h.

References prediction_.

◆ getInputTrainingSet()

std::vector<SVMData> pcl::SVMClassify::getInputTrainingSet ( )

inline

Return the current training set.

Definition at line 429 of file svm_wrapper.h.

References training_set_.

◆ loadClassifierModel()

bool pcl::SVMClassify::loadClassifierModel ( const char * filename )

Read in a classifier model (in svmlight format).

Returns: false if fails

◆ loadClassProblem()

bool pcl::SVMClassify::loadClassProblem ( const char * filename )

inline

Read in a raw classification problem (in svmlight format).

The values are normalized using the classifier model information.

Returns: false if fails

Definition at line 490 of file svm_wrapper.h.

References pcl::SVM::adaptLibSVMToInput(), svm_model::l, pcl::SVM::loadProblem(), model_, prob_, scaleProblem(), scaling_, and training_set_.

◆ loadNormClassProblem()

bool pcl::SVMClassify::loadNormClassProblem ( const char * filename )

inline

Read in a normalized classification problem (in svmlight format).

The data is kept without normalizing.

Returns: false if fails

Definition at line 507 of file svm_wrapper.h.

References pcl::SVM::adaptLibSVMToInput(), pcl::SVM::loadProblem(), prob_, and training_set_.

◆ resetTrainingSet()

void pcl::SVMClassify::resetTrainingSet ( )

inline

Reset the training set.

Definition at line 436 of file svm_wrapper.h.

References training_set_.

◆ saveClassificationResult()

void pcl::SVMClassify::saveClassificationResult ( const char * filename )

Save the classification result in an extern file.

◆ saveClassProblem()

bool pcl::SVMClassify::saveClassProblem ( const char * filename )

inline

Save the raw classification problem in a file (in svmlight format).

Returns: false if fails

Definition at line 550 of file svm_wrapper.h.

References pcl::SVM::saveProblem().

◆ saveNormClassProblem()

bool pcl::SVMClassify::saveNormClassProblem ( const char * filename )

inline

Save the normalized classification problem in a file (in svmlight format).

Returns: false if fails

Definition at line 560 of file svm_wrapper.h.

References prob_, and pcl::SVM::saveProblemNorm().

◆ scaleProblem()

void pcl::SVMClassify::scaleProblem	(	svm_problem &	input,
		svm_scaling	scaling
	)

protected

It scales the input dataset using the model information.

Referenced by loadClassProblem().

◆ setClassifierModel()

void pcl::SVMClassify::setClassifierModel ( SVMModel model )

inline

Set the classifier model.

Definition at line 462 of file svm_wrapper.h.

References svm_node::index, svm_scaling::max, model_, model_extern_copied_, svm_scaling::obj, svm_model::scaling, and scaling_.

◆ setInputTrainingSet()

void pcl::SVMClassify::setInputTrainingSet ( std::vector< SVMData > training_set )

inline

It adds/store the training set with labelled data.

Definition at line 412 of file svm_wrapper.h.

References pcl::SVM::adaptInputToLibSVM(), pcl::SVM::getClassName(), svm_scaling::max, prob_, scaling_, and training_set_.

◆ setProbabilityEstimates()

void pcl::SVMClassify::setProbabilityEstimates ( bool set )

inline

Set whether the classification has to be done with the probability estimate.

(The classifier model has to support it).

Definition at line 517 of file svm_wrapper.h.

References predict_probability_.

Member Data Documentation

◆ class_name_

std::string pcl::SVM::class_name_

protected

Definition at line 130 of file svm_wrapper.h.

Referenced by SVMClassify().

◆ labelled_training_set_

bool pcl::SVM::labelled_training_set_

protected

Definition at line 134 of file svm_wrapper.h.

◆ line_

char* pcl::SVM::line_

protected

Definition at line 132 of file svm_wrapper.h.

◆ max_line_len_

int pcl::SVM::max_line_len_

protected

Definition at line 133 of file svm_wrapper.h.

◆ model_

SVMModel pcl::SVM::model_

protected

Definition at line 126 of file svm_wrapper.h.

Referenced by loadClassProblem(), setClassifierModel(), and ~SVMClassify().

◆ model_extern_copied_

bool pcl::SVMClassify::model_extern_copied_

protected

Initial value:

{

false}

Definition at line 390 of file svm_wrapper.h.

Referenced by setClassifierModel(), and ~SVMClassify().

◆ param_

SVMParam pcl::SVM::param_

protected

Definition at line 129 of file svm_wrapper.h.

◆ predict_probability_

bool pcl::SVMClassify::predict_probability_ {false}

protected

Definition at line 392 of file svm_wrapper.h.

Referenced by setProbabilityEstimates().

◆ prediction_

std::vector<std::vector<double> > pcl::SVMClassify::prediction_

protected

Definition at line 393 of file svm_wrapper.h.

Referenced by getClassificationResult().

◆ prob_

svm_problem pcl::SVM::prob_

protected

Definition at line 125 of file svm_wrapper.h.

Referenced by loadClassProblem(), loadNormClassProblem(), saveNormClassProblem(), and setInputTrainingSet().

◆ scaling_

svm_scaling pcl::SVM::scaling_

protected

Definition at line 127 of file svm_wrapper.h.

Referenced by loadClassProblem(), setClassifierModel(), and setInputTrainingSet().

◆ training_set_

std::vector<SVMData> pcl::SVM::training_set_

protected

Definition at line 124 of file svm_wrapper.h.

Referenced by getInputTrainingSet(), loadClassProblem(), loadNormClassProblem(), resetTrainingSet(), and setInputTrainingSet().

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

pcl/ml/svm_wrapper.h

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ SVMClassify()

◆ ~SVMClassify()

Member Function Documentation

◆ classification() [1/2]

◆ classification() [2/2]

◆ classificationTest()

◆ getClassificationResult()

◆ getInputTrainingSet()

◆ loadClassifierModel()

◆ loadClassProblem()

◆ loadNormClassProblem()

◆ resetTrainingSet()

◆ saveClassificationResult()

◆ saveClassProblem()

◆ saveNormClassProblem()

◆ scaleProblem()

◆ setClassifierModel()

◆ setInputTrainingSet()

◆ setProbabilityEstimates()

Member Data Documentation

◆ class_name_

◆ labelled_training_set_

◆ line_

◆ max_line_len_

◆ model_

◆ model_extern_copied_

◆ param_

◆ predict_probability_

◆ prediction_

◆ prob_

◆ scaling_

◆ training_set_