PndLVQTrain Class Reference

Interface definition for LVQ trainers. More...

#include <PndLVQTrain.h>

Inheritance diagram for PndLVQTrain:

Public Member Functions
	PndLVQTrain (std::vector< std::pair< std::string, std::vector< float > *>> const &InputEvtsParam, std::vector< std::string > const &ClassNames, std::vector< std::string > const &VarNames, bool trim=false)
	PndLVQTrain (std::string const &InPut, std::vector< std::string > const &ClassNames, std::vector< std::string > const &VarNames, bool trim=true)
virtual	~PndLVQTrain ()
void	storeWeights ()
void	Train ()
void	Train21 ()
void	setProtoInitType (ProtoInitType iniTypeVal=RAND_FROM_DATA)
void	SetInitProtoFileName (std::string const &fileName)
void	SetLearnPrameters (double const initConst, double const etZ, double const etF, unsigned int const Nswp)
void	SetNumberOfProto (size_t const numProto)
void	SetNumberOfProto (std::map< std::string, size_t > const &labelMap)
void	SetErrorStepSize (unsigned int const val=1000)
void	SetLVQ2_1WindowSize (float const Wsize=0.3)
void	EvalClassifierError ()
void	SetPerEpochEval (bool val)
bool	GetPerEpochEval () const
Public Member Functions inherited from PndMvaTrainer
	PndMvaTrainer (std::vector< std::pair< std::string, std::vector< float > *>> const &InputEvtsParam, std::vector< std::string > const &ClassNames, std::vector< std::string > const &VarNames, bool trim=true)
	PndMvaTrainer (std::string const &InPut, std::vector< std::string > const &ClassNames, std::vector< std::string > const &VarNames, bool trim=true)
virtual	~PndMvaTrainer ()
	Destructor. More...
void	SetTestSetSize (size_t percent=50)
void	SetTestSet (std::set< size_t > const &testSet)
void	NormalizeData (NormType t=NONORM)
void	PCATransForm ()
void	SetOutPutFile (std::string const &outFile)
void	WriteErroVect (std::string const &FileName) const
std::vector< StepError > const &	GetErrorValues () const
virtual void	Initialize ()
std::set< size_t > const &	GetTestEvetIdx () const
std::vector< PndMvaClass > const &	GetClasses () const
	Get the list of available classes (labels). More...
std::vector< PndMvaVariable > const &	GetVariables () const
	Get the list of available variables. More...
size_t	GetRndSeed () const
void	SetRndSeed (size_t const sd)

Additional Inherited Members
Protected Member Functions inherited from PndMvaTrainer
void	SetAppType (AppType t)
void	WriteToWeightFile (std::vector< std::pair< std::string, std::vector< float > *>> const &weights) const
void	splitTetsSet ()
Protected Attributes inherited from PndMvaTrainer
std::set< size_t >	m_testSet_indices
	Indices of the test set. More...
PndMvaDataSet	m_dataSets
	Data set. Holds event values. More...
std::vector< StepError >	m_StepErro
	Container to keep per step error values. More...
std::string	m_outFile
	Output filename. More...
size_t	m_RND_seed
	Random seed. More...

Detailed Description

Interface definition for LVQ trainers.

Definition at line 33 of file PndLVQTrain.h.

Constructor & Destructor Documentation

PndLVQTrain() [1/2]

PndLVQTrain::PndLVQTrain ( std::vector< std::pair< std::string, std::vector< float > *>> const &  InputEvtsParam, std::vector< std::string > const &  ClassNames, std::vector< std::string > const &  VarNames, bool  trim = false  )

explicit

Constructor:

Parameters

InputEvtsParam	Input events vector.
ClassNames	class names.
VarNames	variable names of the features.

PndLVQTrain() [2/2]

PndLVQTrain::PndLVQTrain ( std::string const &  InPut, std::vector< std::string > const &  ClassNames, std::vector< std::string > const &  VarNames, bool  trim = true  )

explicit

Constructor:

Parameters

InPut	Input file name.
ClassNames	class names.
VarNames	variable names of the features.

~PndLVQTrain()

virtual PndLVQTrain::~PndLVQTrain ( )

virtual

Destructor

Member Function Documentation

EvalClassifierError()

void PndLVQTrain::EvalClassifierError ( )

virtual

Classifier evaluation.

Reimplemented from PndMvaTrainer.

GetPerEpochEval()

bool PndLVQTrain::GetPerEpochEval ( ) const

inline

Getter for evaluation scheme.

Returns

Per epoch or per step.

Definition at line 298 of file PndLVQTrain.h.

{
  return m_PerEpoch;
};

SetErrorStepSize()

void PndLVQTrain::SetErrorStepSize ( unsigned int const  val = 1000 )

inline

Set how often the classifier has to be evaluated.

Parameters

val	Evaluate after #val steps. If (Val == 0) then the classifier is evaluated once at the end of the training prodecure.

Definition at line 283 of file PndLVQTrain.h.

{
  m_ErrorStep = val;
};

SetInitProtoFileName()

void PndLVQTrain::SetInitProtoFileName ( std::string const &  fileName )

inline

Set the file name which holds the pre-initialized code books.

Parameters

val	The name of the file which containes the pre initialized code books.

Definition at line 270 of file PndLVQTrain.h.

{
  m_initProtoFile = fileName;
};

SetLearnPrameters()

void PndLVQTrain::SetLearnPrameters ( double const  initConst, double const  etZ, double const  etF, unsigned int const  Nswp  )

inline

Sets the learning parameters.

Parameters

initConst	Initialization constant, used to initialize LVQ prototypes.
etZ	EthaZero, start value for the learning rate.
etF	Final value for Etha (learning rate)
Nswp	Number of sweeps through the examples collection set.

Definition at line 275 of file PndLVQTrain.h.

{
  m_initConst = initConst;
  m_ethaZero = etZ;
  m_ethaFinal = etF;
  m_NumSweep = Nswp;
};

SetLVQ2_1WindowSize()

void PndLVQTrain::SetLVQ2_1WindowSize ( float const  Wsize = 0.3 )

inline

Set the window size for LVQ2.1 alg. A value between 0.2 & 0.3 is recommended.

Definition at line 288 of file PndLVQTrain.h.

{
  m_WindowSize = Wsize;
};

SetNumberOfProto() [1/2]

void PndLVQTrain::SetNumberOfProto

(

size_t const

numProto

)

Set the number of protoTypes to be used for training. The same number of prototypes are initialized for all available labels(classes).

Parameters

numProto

Number of prototypes.

SetNumberOfProto() [2/2]

void PndLVQTrain::SetNumberOfProto

(

std::map< std::string, size_t > const &

labelMap

)

Set the number of protoTypes to be used for training.

Parameters

labelMap

Map containing number of prototypes for each class (label).

SetPerEpochEval()

void PndLVQTrain::SetPerEpochEval ( bool  val )

inline

Select if we want to follow the training evaluation per epoch (sweeps) or per step. The number of steps = Sweeps * (#examples).

Parameters

val	true = evaluate per epoch, false per step. Default is false.

Definition at line 293 of file PndLVQTrain.h.

{
  m_PerEpoch = val;
};

setProtoInitType()

void PndLVQTrain::setProtoInitType ( ProtoInitType  iniTypeVal = RAND_FROM_DATA )

inline

Set CodeBook init type.

Parameters

iniTypeVal

Initialization type.

Definition at line 265 of file PndLVQTrain.h.

{
  m_proto_init = iniTypeVal;
};

storeWeights()

void PndLVQTrain::storeWeights ( )

virtual

Store weights in the output File. If output file name is not specified, then write nothing.

Implements PndMvaTrainer.

Train()

void PndLVQTrain::Train ( )

virtual

Train the classifier accourding to LVQ1 algorithm.

Implements PndMvaTrainer.

Train21()

void PndLVQTrain::Train21

(

)

Train the classifier accourding to LVQ2.1 algorithm.

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

• PndLVQTrain.h