KKMLL::CrossValidationVoting Class Reference

#include <CrossValidationVoting.h>

Public Member Functions
	CrossValidationVoting (TrainingConfiguration2ListPtr _configs, FeatureVectorListPtr _examples, MLClassListPtr _mlClasses, kkint32 _numOfFolds, bool _featuresAreAlreadyNormalized, FileDescPtr _fileDesc)
	~CrossValidationVoting ()
float	Accuracy ()
double	ClassificationTime () const
ConfusionMatrix2Ptr	ConfussionMatrix ()
float	FoldAccuracy (kkint32 foldNum) const
KKStr	FoldAccuracysToStr () const
KKStr	FoldStr () const
kkint32	NumOfSupportVectors () const
void	RunCrossValidation (RunLog &log)
void	RunValidationOnly (FeatureVectorListPtr validationData, bool *classedCorrectly, RunLog &log)
double	TrainingTime () const

Detailed Description

Definition at line 55 of file CrossValidationVoting.h.

Constructor & Destructor Documentation

CrossValidationVoting::CrossValidationVoting	(	TrainingConfiguration2ListPtr	_configs,
		FeatureVectorListPtr	_examples,
		MLClassListPtr	_mlClasses,
		kkint32	_numOfFolds,
		bool	_featuresAreAlreadyNormalized,
		FileDescPtr	_fileDesc
	)

Definition at line 31 of file CrossValidationVoting.cpp.

References KKMLL::FeatureVectorList::ExtractExamplesForClassList().

                                              :

   configs                      (_configs),
   featuresAreAlreadyNormalized (_featuresAreAlreadyNormalized),
   fileDesc                     (_fileDesc),
   foldAccuracies               (NULL),
   foldCounts                   (NULL),
   confusionMatrix              (NULL),
   cmByNumOfConflicts           (NULL),
   examples                     (NULL),
   mlClasses                    (_mlClasses),
   examplesPerClass             (0),
   maxNumOfConflicts            (0),
   numOfFolds                   (_numOfFolds),
   numOfSupportVectors          (0),
   numOfWinnersCounts           (NULL),
   numOfWinnersCorrects         (NULL),
   numOfWinnersOneOfTheWinners  (NULL),
   classificationTime           (0.0),
   trainingTime                 (0.0)
 
{
  examples = _examples->ExtractExamplesForClassList (mlClasses);
  examplesPerClass = 999999;
}

CrossValidationVoting::~CrossValidationVoting

(

)

Definition at line 65 of file CrossValidationVoting.cpp.

{
  DeleteAllocatedMemory ();
  delete  examples;  examples = NULL;
}

Member Function Documentation

float CrossValidationVoting::Accuracy

(

)

Definition at line 467 of file CrossValidationVoting.cpp.

References KKMLL::ConfusionMatrix2::Accuracy().

{
  if  (confusionMatrix)
    return  (float)confusionMatrix->Accuracy ();
  else
    return 0.0;
}  /* Accuracy */

double KKMLL::CrossValidationVoting::ClassificationTime ( ) const

inline

Definition at line 79 of file CrossValidationVoting.h.

{return  classificationTime;}

ConfusionMatrix2Ptr KKMLL::CrossValidationVoting::ConfussionMatrix ( )

inline

Definition at line 76 of file CrossValidationVoting.h.

{return  confusionMatrix;}

float CrossValidationVoting::FoldAccuracy

(

kkint32

foldNum

)

const

Definition at line 496 of file CrossValidationVoting.cpp.

{
  if  (!foldAccuracies)
    return 0.0f;

  if  ((foldNum < 0)  ||  (foldNum >= numOfFolds))
    return 0.0f;

  return  foldAccuracies[foldNum];
}  /* FoldAccuracy */

KKStr CrossValidationVoting::FoldAccuracysToStr

(

)

const

Definition at line 478 of file CrossValidationVoting.cpp.

References KKB::KKStr::Concat(), KKB::KKStr::KKStr(), and KKB::StrFormatDouble().

{
  KKStr  foldAccuracyStr (9 * numOfFolds);  // Pre Reserving enough space for all Accuracies.

  for  (kkint32 foldNum = 0;  foldNum < numOfFolds;  foldNum++)
  {
    if  (foldNum > 0)
      foldAccuracyStr << "\t";
    foldAccuracyStr << StrFormatDouble (foldAccuracies[foldNum], "ZZ,ZZ0.00%");
  }

  return  foldAccuracyStr;
}  /* FoldAccuracysToStr */

KKStr CrossValidationVoting::FoldStr

(

)

const

Definition at line 510 of file CrossValidationVoting.cpp.

References KKB::KKStr::Concat(), and KKB::KKStr::KKStr().

{
  if  ((numOfFolds <= 0)  ||  (!foldAccuracies))
    return  "";

  kkint32  x;

  KKStr  result (numOfFolds + 10);

  for  (x = 0;  x < numOfFolds;  x++)
  {
    if  (x > 0)
      result << ",";
    result << foldAccuracies[x];
  }

  return  result;
}  /* FoldStr */

kkint32 KKMLL::CrossValidationVoting::NumOfSupportVectors ( ) const

inline

Definition at line 83 of file CrossValidationVoting.h.

{return  numOfSupportVectors;}

void CrossValidationVoting::RunCrossValidation

(

RunLog &

log

)

Definition at line 144 of file CrossValidationVoting.cpp.

References KKMLL::FeatureVectorList::ManufactureEmptyList(), and KKMLL::FeatureVectorList::PushOnBack().

{
  log.Level (10) << "CrossValidationVoting::RunCrossValidationVoting" << endl;

  if  (numOfFolds < 1)
  {
    log.Level (-1) << endl
                   << endl
                   << "CrossValidationVoting::RunCrossValidationVoting     **** ERROR ****" << endl
                   << endl
                   << "                                  Invalid  numOfFolds[" << numOfFolds << "]." << endl
                   << endl;
    return;
  }

  DeleteAllocatedMemory ();
  AllocateMemory (log);

  kkint32  imageCount       = examples->QueueSize ();
  kkint32  numImagesPerFold = (imageCount + numOfFolds - 1) / numOfFolds;
  kkint32  firstInGroup     = 0;

  kkint32  foldNum;

  for  (foldNum = 0;  foldNum < numOfFolds;  foldNum++)
  {
    kkint32  lastInGroup;

    // If We are doing the last Fold Make sure that we are including all the examples 
    // that have not been tested.
    if  (foldNum == (numOfFolds - 1))
      lastInGroup = imageCount;
    else
      lastInGroup = firstInGroup + numImagesPerFold - 1;


    cout << "Fold [" << (foldNum + 1) << "]  of  [" << numOfFolds << "]" << endl;

    FeatureVectorListPtr  trainingExamples = examples->ManufactureEmptyList (true);
    FeatureVectorListPtr  testImages       = examples->ManufactureEmptyList (true);

    log.Level (30) << "Fold Num["        << foldNum        << "]   "
                   << "FirstTestImage["  << firstInGroup   << "]   "
                   << "LastInGroup["     << lastInGroup    << "]."
                   << endl;

    for  (kkint32  x = 0; x < imageCount; x++)
    {
      FeatureVectorPtr  newImage = examples->IdxToPtr (x)->Duplicate ();
      if  ((x >= firstInGroup)  &&  (x <= lastInGroup))
        testImages->PushOnBack (newImage);
      else
        trainingExamples->PushOnBack (newImage);
    }

    cout << "Number Of Training Images : " << trainingExamples->QueueSize () << endl;
    cout << "Number Of Test Images     : " << testImages->QueueSize ()     << endl;

    CrossValidate (testImages, trainingExamples, foldNum, NULL, log);

    delete  trainingExamples;  trainingExamples = NULL;
    delete  testImages;        testImages       = NULL;
    firstInGroup = firstInGroup + numImagesPerFold;
  }
}  /* RunCrossValidationVoting */

void CrossValidationVoting::RunValidationOnly	(	FeatureVectorListPtr	validationData,
		bool *	classedCorrectly,
		RunLog &	log
	)

Definition at line 214 of file CrossValidationVoting.cpp.

References KKMLL::FeatureVectorList::DuplicateListAndContents().

{
  log.Level (10) << "CrossValidationVoting::RunValidationOnly" << endl;
  DeleteAllocatedMemory ();
  AllocateMemory (log);

  // We need to get a duplicate copy of each image data because the trainer and classifier
  // will normalize the data.
  FeatureVectorListPtr  trainingExamples = examples->DuplicateListAndContents ();
  FeatureVectorListPtr  testImages       = validationData->DuplicateListAndContents ();

  CrossValidate (testImages, trainingExamples, 0, classedCorrectly, log);

  delete  trainingExamples;
  delete  testImages;
}  /* RunValidationOnly */

double KKMLL::CrossValidationVoting::TrainingTime ( ) const

inline

Definition at line 84 of file CrossValidationVoting.h.

{return  trainingTime;}

---

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

• C:/Users/Kurt/GitHub/KSquareLibraries/KKMachineLearning/CrossValidationVoting.h
• C:/Users/Kurt/GitHub/KSquareLibraries/KKMachineLearning/CrossValidationVoting.cpp