Point Cloud Library (PCL)  1.12.1-dev
List of all members | Public Member Functions | Protected Member Functions | Protected Attributes
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:
+ Collaboration 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< SVMDatagetInputTrainingSet ()
 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< SVMDatatraining_set_
 
- Protected Attributes inherited from pcl::SVM
std::vector< SVMDatatraining_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 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 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 model_.

◆ getInputTrainingSet()

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

Return the current training set.

Definition at line 310 of file svm_wrapper.h.

References training_set_.

◆ getParameters()

SVMParam pcl::SVMTrain::getParameters ( )
inline

Return the current training parameters.

Definition at line 289 of file svm_wrapper.h.

References 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 prob_.

◆ resetTrainingSet()

void pcl::SVMTrain::resetTrainingSet ( )
inline

Reset the training set.

Definition at line 317 of file svm_wrapper.h.

References 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 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 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 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.

Referenced by SVMTrain().

◆ 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.

Referenced by getClassifierModel(), and ~SVMTrain().

◆ 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.

Referenced by getParameters(), and setParameters().

◆ prob_

svm_problem pcl::SVM::prob_
protected

Definition at line 124 of file svm_wrapper.h.

Referenced by loadProblem(), and saveNormTrainingSet().

◆ 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.

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


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