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PndMvaSomTrainer Class Reference

#include <PndMvaSOMTrainer.h>

Public Member Functions

 PndMvaSomTrainer (DataPoints const *const InputData, size_t mapWidth, size_t mapHeight, size_t numIter, MapNodeInitType initType=SOM_RAND_FROM_DATA, GridInitType gridInitType=RECTANGULAR)
 
virtual ~PndMvaSomTrainer ()
 
virtual void InitMap ()
 
virtual void TrainBatch ()
 
virtual void TrainOnline ()
 
virtual void Calibrate ()
 
std::vector< PndSomNode * > const & GetTheMap () const
 
DataPoints const & GetInputDataSet () const
 
size_t GetNumNodes () const
 
void SetSigmaZero (double val)
 
double GetSigmaZero () const
 
void SetLambda (double val)
 
double GetLambda () const
 
void SetNodeInitType (MapNodeInitType val=SOM_RAND_FROM_DATA)
 
MapNodeInitType GetNodeInitType () const
 
size_t GetMapHeight () const
 
void SetMapHeight (size_t val)
 
size_t GetMapWidth () const
 
void SetMapWidth (size_t val)
 
size_t GetNumIterations () const
 
void SetNumIterations (size_t val)
 

Protected Member Functions

void printMapGrid () const
 

Detailed Description

Definition at line 45 of file PndMvaSOMTrainer.h.

Constructor & Destructor Documentation

◆ PndMvaSomTrainer()

PndMvaSomTrainer::PndMvaSomTrainer ( DataPoints const *const  InputData,
size_t  mapWidth,
size_t  mapHeight,
size_t  numIter,
MapNodeInitType  initType = SOM_RAND_FROM_DATA,
GridInitType  gridInitType = RECTANGULAR 
)
explicit

Constructor.

Parameters
InputDataInput Data points.
mapWidthThe width of the SOM.
mapHeightThe height of the SOM.
numIterNumber of learning iterations.
initTypeThe scheme to initialize weight of each node.

◆ ~PndMvaSomTrainer()

virtual PndMvaSomTrainer::~PndMvaSomTrainer ( )
virtual

Destructor.

Member Function Documentation

◆ Calibrate()

virtual void PndMvaSomTrainer::Calibrate ( )
virtual

Calibrate the map (post labeling). The current implementation uses the winner takes all scheme. The label with the largest count determines the node label. Note that also a list of all labels is kept in de node itself.

◆ GetInputDataSet()

DataPoints const & PndMvaSomTrainer::GetInputDataSet ( ) const
inline

Get the input data set.

Returns
The list of input data points.

Definition at line 208 of file PndMvaSOMTrainer.h.

209 {
210  return (*(this->m_DataSet));
211 };

◆ GetLambda()

double PndMvaSomTrainer::GetLambda ( ) const
inline

Definition at line 233 of file PndMvaSOMTrainer.h.

234 {
235  return this->m_lambda;
236 };

◆ GetMapHeight()

size_t PndMvaSomTrainer::GetMapHeight ( ) const
inline

Map size.

Definition at line 243 of file PndMvaSOMTrainer.h.

244 {
245  return this->m_MapHeight;
246 };

◆ GetMapWidth()

size_t PndMvaSomTrainer::GetMapWidth ( ) const
inline

Definition at line 253 of file PndMvaSOMTrainer.h.

254 {
255  return this->m_MapWidth;
256 };

◆ GetNodeInitType()

MapNodeInitType PndMvaSomTrainer::GetNodeInitType ( ) const
inline

Definition at line 238 of file PndMvaSOMTrainer.h.

239 {
240  return this->m_InitMode;
241 };

◆ GetNumIterations()

size_t PndMvaSomTrainer::GetNumIterations ( ) const
inline

Number of iteration (epochs, learning steps).

Definition at line 268 of file PndMvaSOMTrainer.h.

269 {
270  return this->m_NumIterations;
271 };

◆ GetNumNodes()

size_t PndMvaSomTrainer::GetNumNodes ( ) const
inline
Returns
The total number of map nodes.

Definition at line 263 of file PndMvaSOMTrainer.h.

264 {
265  return (this->m_MapWidth * this->m_MapHeight);
266 };

◆ GetSigmaZero()

double PndMvaSomTrainer::GetSigmaZero ( ) const
inline

Definition at line 228 of file PndMvaSOMTrainer.h.

229 {
230  return this->m_sigmaZero;
231 };

◆ GetTheMap()

std::vector< PndSomNode * > const & PndMvaSomTrainer::GetTheMap ( ) const
inline
Returns
The actual SOM.

Definition at line 203 of file PndMvaSOMTrainer.h.

204 {
205  return this->m_TheMap;
206 };

◆ InitMap()

virtual void PndMvaSomTrainer::InitMap ( )
virtual

Initialize the map according to the given scheme.

◆ printMapGrid()

void PndMvaSomTrainer::printMapGrid ( ) const
protected

◆ SetLambda()

void PndMvaSomTrainer::SetLambda ( double  val)
inline

Set initial value for lambda.

Definition at line 218 of file PndMvaSOMTrainer.h.

219 {
220  this->m_lambda = val;
221 };

◆ SetMapHeight()

void PndMvaSomTrainer::SetMapHeight ( size_t  val)
inline

Definition at line 248 of file PndMvaSOMTrainer.h.

249 {
250  this->m_MapHeight = val;
251 };

◆ SetMapWidth()

void PndMvaSomTrainer::SetMapWidth ( size_t  val)
inline

Definition at line 258 of file PndMvaSOMTrainer.h.

259 {
260  this->m_MapWidth = val;
261 };

◆ SetNodeInitType()

void PndMvaSomTrainer::SetNodeInitType ( MapNodeInitType  val = SOM_RAND_FROM_DATA)
inline

Set initialization method.

Definition at line 223 of file PndMvaSOMTrainer.h.

224 {
225  this->m_InitMode = val;
226 };

◆ SetNumIterations()

void PndMvaSomTrainer::SetNumIterations ( size_t  val)
inline

Definition at line 273 of file PndMvaSOMTrainer.h.

274 {
275  this->m_NumIterations = val;
276 };

◆ SetSigmaZero()

void PndMvaSomTrainer::SetSigmaZero ( double  val)
inline

Set initial value for sigma.

Definition at line 213 of file PndMvaSOMTrainer.h.

214 {
215  this->m_sigmaZero = val;
216 };

◆ TrainBatch()

virtual void PndMvaSomTrainer::TrainBatch ( )
virtual

Train map using batch schema. All available data vectors are presented at once.

◆ TrainOnline()

virtual void PndMvaSomTrainer::TrainOnline ( )
virtual

Train the map using Online scheme. Data vectors are presented one at a time.


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