Point Cloud Library (PCL): pcl::SVMTrain Class Reference

SVM (Support Vector Machines) training class for the SVM machine learning. More...

#include <pcl/ml/svm_wrapper.h>

Inheritance diagram for pcl::SVMTrain:

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

	~SVMTrain ()
	Destructor. More...

void	setParameters (SVMParam param)
	Change default training parameters (pcl::SVMParam). More...

SVMParam	getParameters ()
	Return the current training parameters. More...

SVMModel	getClassifierModel ()
	Return the result of the training. 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	trainClassifier ()
	Start the training of the SVM classifier. More...

bool	loadProblem (const char *filename)
	Read in a problem (in svmlight format). More...

void	setDebugMode (bool in)
	Set to 1 for debugging info. More...

bool	saveTrainingSet (const char *filename)
	Save the raw training set in a file (in svmlight format). More...

bool	saveNormTrainingSet (const char *filename)
	Save the normalized training set 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	doCrossValidation ()
	To cross validate the classifier. More...

void	scaleFactors (std::vector< SVMData > training_set, svm_scaling &scaling)
	It extracts scaling factors from the input training_set. 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	debug_
	Set to 1 to see the training output. More...

int	cross_validation_
	Set too 1 for cross validating the classifier. More...

int	nr_fold_
	Number of folds to be used during cross validation. More...

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_

int	max_line_len_

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) training class for the SVM machine learning.

It creates a model for the classifier from a labelled input dataset.

OPTIONAL: pcl::SVMParam has to be given as input to vary the default training method and parameters.

Definition at line 233 of file svm_wrapper.h.

Constructor & Destructor Documentation

◆ SVMTrain()

pcl::SVMTrain::SVMTrain ( )

inline

Constructor.

Definition at line 266 of file svm_wrapper.h.

References pcl::SVM::class_name_, and pcl::SVM::printNull().

◆ ~SVMTrain()

pcl::SVMTrain::~SVMTrain ( )

inline

Destructor.

Definition at line 274 of file svm_wrapper.h.

References svm_model::l, and pcl::SVM::model_.

Member Function Documentation

◆ doCrossValidation()

void pcl::SVMTrain::doCrossValidation ( )

protected

To cross validate the classifier.

It is automatic for probability estimate.

◆ getClassifierModel()

SVMModel pcl::SVMTrain::getClassifierModel ( )

inline

Return the result of the training.

Definition at line 296 of file svm_wrapper.h.

References pcl::SVM::model_.

◆ getInputTrainingSet()

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

inline

Return the current training set.

Definition at line 310 of file svm_wrapper.h.

References pcl::SVM::training_set_.

◆ getParameters()

SVMParam pcl::SVMTrain::getParameters ( )

inline

Return the current training parameters.

Definition at line 289 of file svm_wrapper.h.

References pcl::SVM::param_.

◆ loadProblem()

bool pcl::SVMTrain::loadProblem ( const char * filename )

inline

Read in a problem (in svmlight format).

Returns: false if fails

Definition at line 334 of file svm_wrapper.h.

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

◆ resetTrainingSet()

void pcl::SVMTrain::resetTrainingSet ( )

inline

Reset the training set.

Definition at line 317 of file svm_wrapper.h.

References pcl::SVM::training_set_.

◆ saveNormTrainingSet()

bool pcl::SVMTrain::saveNormTrainingSet ( const char * filename )

inline

Save the normalized training set in a file (in svmlight format).

Returns: false if fails

Definition at line 366 of file svm_wrapper.h.

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

◆ saveTrainingSet()

bool pcl::SVMTrain::saveTrainingSet ( const char * filename )

inline

Save the raw training set in a file (in svmlight format).

Returns: false if fails

Definition at line 356 of file svm_wrapper.h.

References pcl::SVM::saveProblem().

◆ scaleFactors()

void pcl::SVMTrain::scaleFactors	(	std::vector< SVMData >	training_set,
		svm_scaling &	scaling
	)

protected

It extracts scaling factors from the input training_set.

The scaling of the training_set is a mandatory for a good training of the classifier.

◆ setDebugMode()

void pcl::SVMTrain::setDebugMode ( bool in )

inline

Set to 1 for debugging info.

Definition at line 341 of file svm_wrapper.h.

References debug_, and pcl::SVM::printNull().

◆ setInputTrainingSet()

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

inline

It adds/store the training set with labelled data.

Definition at line 303 of file svm_wrapper.h.

References pcl::SVM::training_set_.

◆ setParameters()

void pcl::SVMTrain::setParameters ( SVMParam param )

inline

Change default training parameters (pcl::SVMParam).

Definition at line 282 of file svm_wrapper.h.

References pcl::SVM::param_.

◆ trainClassifier()

bool pcl::SVMTrain::trainClassifier ( )

Start the training of the SVM classifier.

Returns: false if fails

Member Data Documentation

◆ class_name_

std::string pcl::SVM::class_name_

protected

Definition at line 129 of file svm_wrapper.h.

◆ cross_validation_

int pcl::SVMTrain::cross_validation_

protected

Set too 1 for cross validating the classifier.

Definition at line 248 of file svm_wrapper.h.

◆ debug_

bool pcl::SVMTrain::debug_

protected

Set to 1 to see the training output.

Definition at line 246 of file svm_wrapper.h.

Referenced by setDebugMode().

◆ labelled_training_set_

bool pcl::SVM::labelled_training_set_

protected

Definition at line 133 of file svm_wrapper.h.

◆ line_

char* pcl::SVM::line_

protected

Definition at line 131 of file svm_wrapper.h.

◆ max_line_len_

int pcl::SVM::max_line_len_

protected

Definition at line 132 of file svm_wrapper.h.

◆ model_

SVMModel pcl::SVM::model_

protected

Definition at line 125 of file svm_wrapper.h.

◆ nr_fold_

int pcl::SVMTrain::nr_fold_

protected

Number of folds to be used during cross validation.

It indicates in how many parts is split the input training set.

Definition at line 251 of file svm_wrapper.h.

◆ param_

SVMParam pcl::SVM::param_

protected

Definition at line 128 of file svm_wrapper.h.

◆ prob_

svm_problem pcl::SVM::prob_

protected

Definition at line 124 of file svm_wrapper.h.

◆ scaling_

svm_scaling pcl::SVM::scaling_

protected

Definition at line 126 of file svm_wrapper.h.

◆ training_set_

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

protected

Definition at line 123 of file svm_wrapper.h.

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

◆ SVMTrain()

◆ ~SVMTrain()

Member Function Documentation

◆ doCrossValidation()

◆ getClassifierModel()

◆ getInputTrainingSet()

◆ getParameters()

◆ loadProblem()

◆ resetTrainingSet()

◆ saveNormTrainingSet()

◆ saveTrainingSet()

◆ scaleFactors()

◆ setDebugMode()

◆ setInputTrainingSet()

◆ setParameters()

◆ trainClassifier()

Member Data Documentation

◆ class_name_

◆ cross_validation_

◆ debug_

◆ labelled_training_set_

◆ line_

◆ max_line_len_

◆ model_

◆ nr_fold_

◆ param_

◆ prob_

◆ scaling_

◆ training_set_