#include <ModelKnn.h>

Inheritance diagram for KKMLL::ModelKnn:

Public Types
typedef ModelKnn *	ModelKnnPtr

Public Types inherited from KKMLL::Model
typedef Model *	ModelPtr

enum	ModelTypes : int { ModelTypes::Null = 0, ModelTypes::OldSVM = 1, ModelTypes::SvmBase = 2, ModelTypes::KNN = 3, ModelTypes::UsfCasCor = 4, ModelTypes::Dual = 5 }

Public Member Functions
	ModelKnn ()

	ModelKnn (FactoryFVProducerPtr _factoryFVProducer)

	ModelKnn (const KKStr &_name, const ModelParamKnn &_param, FactoryFVProducerPtr _factoryFVProducer)

	ModelKnn (const ModelKnn &_madel)

virtual	~ModelKnn ()

virtual ModelKnnPtr	Duplicate () const

virtual ModelTypes	ModelType () const

ModelParamKnnPtr	Param ()

virtual MLClassPtr	Predict (FeatureVectorPtr example, RunLog &log)

virtual void	Predict (FeatureVectorPtr example, MLClassPtr knownClass, MLClassPtr &predClass1, MLClassPtr &predClass2, kkint32 &predClass1Votes, kkint32 &predClass2Votes, double &probOfKnownClass, double &predClass1Prob, double &predClass2Prob, kkint32 &numOfWinners, bool &knownClassOneOfTheWinners, double &breakTie, RunLog &log)

virtual ClassProbListPtr	ProbabilitiesByClass (FeatureVectorPtr example, RunLog &log)

virtual void	ProbabilitiesByClass (FeatureVectorPtr example, const MLClassList &_mlClasses, kkint32 _votes, double _probabilities, RunLog &log)

virtual void	ProbabilitiesByClass (FeatureVectorPtr _example, const MLClassList &_mlClasses, double *_probabilities, RunLog &_log)
	Derives predicted probabilities by class. More...

void	ReadXML (XmlStream &s, XmlTagConstPtr tag, VolConstBool &cancelFlag, RunLog &log)
	To be implemented by derived classes; the parent classes fields will be updated by the derived class calling ReadXMLModelToken. More...

virtual void	TrainModel (FeatureVectorListPtr _trainExamples, bool _alreadyNormalized, bool _takeOwnership, VolConstBool &_cancelFlag, RunLog &_log)
	Performs operations such as FeatureEncoding, and Normalization. The actual training of models occurs in the specific derived implementation of 'Model'. More...

void	WriteXML (const KKStr &varName, ostream &o) const

Public Member Functions inherited from KKMLL::Model
	Model ()

	Model (FactoryFVProducerPtr _factoryFVProducer)
	Use this when you are planning on creating a empty model without parameters. More...

	Model (const KKStr &_name, const ModelParam &_param, FactoryFVProducerPtr _factoryFVProducer)
	Construct a instance of 'Model' using the parameters specified in '_param'. More...

	Model (const Model &_madel)
	Copy Constructor. More...

virtual	~Model ()
	Frees any memory allocated by, and owned by the Model. More...

bool	AlreadyNormalized () const

virtual KKStr	Description () const

const FeatureEncoder2 &	Encoder () const

FactoryFVProducerPtr	FactoryFVProducer () const

virtual FeatureNumListConstPtr	GetFeatureNums () const

virtual kkint32	MemoryConsumedEstimated () const

MLClassListPtr	MLClasses () const

MLClassListPtr	MLClassesNewInstance () const

virtual KKStr	ModelTypeStr () const

const KKStr &	Name () const

void	Name (const KKStr &_name)

virtual bool	NormalizeNominalAttributes () const

ModelParamPtr	Param () const

virtual void	PredictRaw (FeatureVectorPtr example, MLClassPtr &predClass, double &dist)

virtual FeatureVectorPtr	PrepExampleForPrediction (FeatureVectorPtr fv, bool &newExampleCreated)
	Every prediction method in every class that is inherited from this class should call this method before performing there prediction. Such things as Normalization and Feature Encoding. More...

virtual void	ProbabilitiesByClassDual (FeatureVectorPtr example, KKStr &classifier1Desc, KKStr &classifier2Desc, ClassProbListPtr &classifier1Results, ClassProbListPtr &classifier2Results, RunLog &log)
	Only applied to ModelDual classifier. More...

virtual void	RetrieveCrossProbTable (MLClassList &classes, double **crossProbTable, RunLog &log)

const KKStr &	RootFileName () const

void	RootFileName (const KKStr &_rootFileName)

virtual FeatureNumListConstPtr	SelectedFeatures () const

const KKB::DateTime &	TimeSaved () const

double	TrainingTime () const

void	TrainingTimeEnd ()
	Derived classes call this method to stop the clock for 'trainingTime'. More...

void	TrainingTimeStart ()
	Derived classes call this method to start the clock for 'trainingTime'. More...

double	TrianingPrepTime () const

bool	ValidModel () const

void	WriteModelXMLFields (std::ostream &o) const
	The "WriteXML" method in Derived classes call this method to include the parents classes fields in the XML data. More...

virtual void	WriteXML (const KKStr &varName, std::ostream &o) const =0

Additional Inherited Members
Static Public Member Functions inherited from KKMLL::Model
static ModelPtr	CreateAModel (ModelTypes _modelType, const KKStr &_name, const ModelParam &_param, FactoryFVProducerPtr _factoryFVProducer, VolConstBool &_cancelFlag, RunLog &_log)
	A factory method that will instantiate the appropriate class of training model based off '_modelType'. More...

static ModelTypes	ModelTypeFromStr (const KKStr &_modelingTypeStr)

static KKStr	ModelTypeToStr (ModelTypes _modelingType)

Protected Member Functions inherited from KKMLL::Model
void	AddErrorMsg (const KKStr &errMsg, kkint32 lineNum)

void	AllocatePredictionVariables ()

void	DeAllocateSpace ()

void	NormalizeProbabilitiesWithAMinumum (kkint32 numClasses, double *probabilities, double minProbability)

void	ReadXMLModelPost (RunLog &log)

XmlTokenPtr	ReadXMLModelToken (XmlTokenPtr t, RunLog &log)
	Will process any tokens that belong to 'ModelParam' and return NULL ones that are not will be passed back. More...

void	ReduceTrainExamples (RunLog &log)
	Reduces the Training Images down to the size dictated by the 'examplesPerClass' parameter. More...

Protected Attributes inherited from KKMLL::Model
bool	alreadyNormalized

MLClassListPtr	classes

MLClassIndexListPtr	classesIndex

double *	classProbs

double **	crossClassProbTable

kkint32	crossClassProbTableSize

FeatureEncoder2Ptr	encoder

VectorKKStr	errors

FactoryFVProducerPtr	factoryFVProducer

FileDescPtr	fileDesc

NormalizationParmsPtr	normParms

kkint32	numOfClasses

ModelParamPtr	param

KKStr	rootFileName

FeatureVectorListPtr	trainExamples

bool	validModel

kkint32 *	votes

bool	weOwnTrainExamples

Detailed Description

Definition at line 10 of file ModelKnn.h.

Member Typedef Documentation

typedef ModelKnn* KKMLL::ModelKnn::ModelKnnPtr

Definition at line 13 of file ModelKnn.h.

Constructor & Destructor Documentation

ModelKnn::ModelKnn ( )

Definition at line 35 of file ModelKnn.cpp.

References KKMLL::Model::Model().

                    :
   Model (),
   param (NULL)
 {
 }

ModelKnn::ModelKnn ( FactoryFVProducerPtr _factoryFVProducer )

Definition at line 43 of file ModelKnn.cpp.

References KKMLL::Model::Model().

                                                            :
   Model (_factoryFVProducer),
   param (NULL)
 {
 }

ModelKnn::ModelKnn	(	const KKStr &	_name,
		const ModelParamKnn &	_param,
		FactoryFVProducerPtr	_factoryFVProducer
	)

Definition at line 52 of file ModelKnn.cpp.

References KKMLL::Model::Model(), and KKMLL::Model::param.

Referenced by KKMLL::Model::CreateAModel().

                     :
   Model (_name, _param, _factoryFVProducer),
   param (NULL)
 {
   param = dynamic_cast<ModelParamKnnPtr> (Model::param);
 }

ModelKnn::ModelKnn ( const ModelKnn & _madel )

Definition at line 65 of file ModelKnn.cpp.

References KKMLL::Model::Model(), and KKMLL::Model::param.

Referenced by Duplicate().

                                            :
   Model (_model),
   param (NULL)
 {
   param = dynamic_cast<ModelParamKnnPtr> (Model::param);
 }

ModelKnn::~ModelKnn ( )

virtual

Definition at line 74 of file ModelKnn.cpp.

 {
 
 }

Member Function Documentation

ModelKnnPtr ModelKnn::Duplicate ( ) const

virtual

Implements KKMLL::Model.

Definition at line 82 of file ModelKnn.cpp.

References ModelKnn().

 {
   return  new ModelKnn (*this);
 }

virtual ModelTypes KKMLL::ModelKnn::ModelType ( ) const

inlinevirtual

Implements KKMLL::Model.

Definition at line 32 of file ModelKnn.h.

References KKMLL::Model::KNN.

32 {return ModelTypes::KNN;}

KKMLL::Model::ModelTypes::KNN

ModelParamKnnPtr ModelKnn::Param ( )

Definition at line 88 of file ModelKnn.cpp.

 {
   return  param;
 }

MLClassPtr ModelKnn::Predict	(	FeatureVectorPtr	example,
		RunLog &	log
	)

virtual

Implements KKMLL::Model.

Definition at line 94 of file ModelKnn.cpp.

 {
   return NULL;
 }

void ModelKnn::Predict	(	FeatureVectorPtr	example,
		MLClassPtr	knownClass,
		MLClassPtr &	predClass1,
		MLClassPtr &	predClass2,
		kkint32 &	predClass1Votes,
		kkint32 &	predClass2Votes,
		double &	probOfKnownClass,
		double &	predClass1Prob,
		double &	predClass2Prob,
		kkint32 &	numOfWinners,
		bool &	knownClassOneOfTheWinners,
		double &	breakTie,
		RunLog &	log
	)

virtual

Implements KKMLL::Model.

Definition at line 103 of file ModelKnn.cpp.

117 {

118 } /* Predict */

ClassProbListPtr ModelKnn::ProbabilitiesByClass	(	FeatureVectorPtr	example,
		RunLog &	log
	)

virtual

Implements KKMLL::Model.

Definition at line 123 of file ModelKnn.cpp.

References KKMLL::Model::classesIndex, KKMLL::ClassProb::ClassProb(), KKMLL::ClassProbList::ClassProbList(), KKB::KKStr::Concat(), KKMLL::MLClassIndexList::GetMLClass(), KKB::KKException::KKException(), KKMLL::Model::numOfClasses, KKMLL::Model::PrepExampleForPrediction(), and KKMLL::ClassProbList::PushOnBack().

 {
   if  (!classesIndex)
   {
     KKStr errMsg = "ModelKnn::ProbabilitiesByClass   ***ERROR***      (classLabelAssigments == NULL)";
     log.Level (-1) << endl << endl << errMsg << endl << endl;
     throw KKException (errMsg);
   }
 
   bool  newExampleCreated = false;
   FeatureVectorPtr  encodedExample = PrepExampleForPrediction (example, newExampleCreated);
 
   //  double  y = SVM289::svm_predict_probability (svmModel,  *encodedExample, classProbs, votes);
 
   if  (newExampleCreated)
   {
     delete encodedExample;
     encodedExample = NULL;
   }
 
   ClassProbListPtr  results = new ClassProbList ();
   kkint32 idx;
   for  (idx = 0;  idx < numOfClasses;  idx++)
   {
     MLClassPtr  ic = classesIndex->GetMLClass (idx);
     results->PushOnBack (new ClassProb (ic, 0.0, 0.0f));
   }
 
   return  results;
 }  /* ProbabilitiesByClass */

void ModelKnn::ProbabilitiesByClass	(	FeatureVectorPtr	example,
		const MLClassList &	_mlClasses,
		kkint32 *	_votes,
		double *	_probabilities,
		RunLog &	log
	)

virtual

Implements KKMLL::Model.

Definition at line 159 of file ModelKnn.cpp.

165 {

166 }

void ModelKnn::ProbabilitiesByClass	(	FeatureVectorPtr	_example,
		const MLClassList &	_mlClasses,
		double *	_probabilities,
		RunLog &	_log
	)

virtual

Derives predicted probabilities by class.

Will get the probabilities assigned to each class by the classifier. The '_mlClasses' parameter dictates the order of the classes. That is the probabilities for any given index in '_probabilities' will be for the class specified in the same index in '_mlClasses'.

Parameters

[in]	_example	FeatureVector object to calculate predicted probabilities for.
[in]	_mlClasses	List image classes that caller is aware of. This should be the same list that was used when constructing this Model object. The list must be the same but not necessarily in the same order as when Model was 1st constructed.
[out]	_probabilities	An array that must be as big as the number of classes as in mlClasses. The probability of class in mlClasses[x] will be returned in probabilities[x].

Implements KKMLL::Model.

Definition at line 169 of file ModelKnn.cpp.

174 {

175 } /* ProbabilitiesByClass */

void ModelKnn::ReadXML	(	XmlStream &	s,
		XmlTagConstPtr	tag,
		VolConstBool &	cancelFlag,
		RunLog &	log
	)

virtual

To be implemented by derived classes; the parent classes fields will be updated by the derived class calling ReadXMLModelToken.

Implements KKMLL::Model.

Definition at line 225 of file ModelKnn.cpp.

References KKMLL::Model::AddErrorMsg(), KKB::KKStr::Concat(), KKB::XmlStream::GetNextToken(), KKB::KKStr::KKStr(), KKMLL::ModelParam::ModelParamTypeStr(), KKMLL::Model::param, KKMLL::Model::ReadXMLModelPost(), KKMLL::Model::ReadXMLModelToken(), and KKB::XmlToken::VarName().

 {
   XmlTokenPtr  t = s.GetNextToken (cancelFlag, log);
   while  (t  &&  (!cancelFlag))
   {
     t = ReadXMLModelToken (t, log);
     if  (t)
     {
       const KKStr&  varName = t->VarName ();
 
       if  ((varName.EqualIgnoreCase ("Param"))  &&  (typeid (*t) == typeid (XmlElementModelParamKnn)))
       {
         delete  param;
         param = dynamic_cast<XmlElementModelParamKnnPtr> (t)->TakeOwnership ();
       }
       else
       {
         KKStr  errMsg (256);
         errMsg << "Invalid XmlElement Encountered:  Section: " << t->SectionName () << "  VarName: " << varName;
         log.Level (-1) << endl << errMsg << endl << endl;
         AddErrorMsg (errMsg, 0);
       }
     }
     delete  t;
     t = s.GetNextToken (cancelFlag, log);
   }
 
   delete  t;
   t = NULL;
 
   if  (!param)
     param = dynamic_cast<ModelParamKnnPtr> (Model::param);
 
   if  (Model::param == NULL)
   {
     KKStr errMsg (128);
     errMsg << "ModelKnn::ReadXML  ***ERROR***  Base class 'Model' does not have 'param' defined.";
     AddErrorMsg (errMsg, 0);
     log.Level (-1) << endl << errMsg << endl << endl;
   }
 
   else if  (typeid (*Model::param) != typeid(ModelParamKnn))
   {
     KKStr errMsg (128);
     errMsg << "ModelKnn::ReadXML  ***ERROR***  Base class 'Model' param parameter is of the wrong type;  found: " << Model::param->ModelParamTypeStr ();
     AddErrorMsg (errMsg, 0);
     log.Level (-1) << endl << errMsg << endl << endl;
   }
 
   else
   {
     param = dynamic_cast<ModelParamKnnPtr> (Model::param);
   }
 
   ReadXMLModelPost (log);
 }  /* ReadXML */

void ModelKnn::TrainModel	(	FeatureVectorListPtr	_trainExamples,
		bool	_alreadyNormalized,
		bool	_takeOwnership,
		VolConstBool &	_cancelFlag,
		RunLog &	_log
	)

virtual

Performs operations such as FeatureEncoding, and Normalization. The actual training of models occurs in the specific derived implementation of 'Model'.

Performs operations such as FeatureEncoding, and Normalization; the actual training of models occurs in the specific implementation of 'Model'.

Parameters

[in]	_trainExamples	Training data that classifier will be built from. If the examples need to be normalized or encoded and we are not taking ownership then a duplicate list of examples will be created that this method and class will be free to modify.
[in]	_alreadyNormalized	Indicates if contents of '_trainExamples' are normalized already; if not they will be normalized.
[in]	_takeOwnership	This instance of Model will take ownership of '_examples' and is free to modify its contents.

Parameters

_takeOwnership Model will take ownership of these examples

Reimplemented from KKMLL::Model.

Definition at line 180 of file ModelKnn.cpp.

References KKMLL::Model::TrainModel(), and KKMLL::Model::validModel.

 {
   _log.Level (20) << "ModelKnn::TrainModel    alreadyNormalized[" << _alreadyNormalized << "]  _takeOwnership[" << _takeOwnership << "]." << endl;
 
   try
   {
     Model::TrainModel (_trainExamples, _alreadyNormalized, _takeOwnership, _cancelFlag, _log);
   }
   catch  (const KKException& e)
   {
     validModel = false;
     throw e;
   }
 }  /* TrainModel */

void ModelKnn::WriteXML	(	const KKStr &	varName,
		ostream &	o
	)		const

Definition at line 202 of file ModelKnn.cpp.

References KKB::XmlTag::AddAtribute(), KKB::KKStr::Empty(), KKB::XmlTag::tagEnd, KKB::XmlTag::tagStart, KKMLL::Model::WriteModelXMLFields(), KKMLL::ModelParamKnn::WriteXML(), KKB::XmlTag::WriteXML(), and KKB::XmlTag::XmlTag().

 {
   XmlTag  startTag ("ModelParamDual",  XmlTag::TagTypes::tagStart);
   if  (!varName.Empty ())
     startTag.AddAtribute ("VarName", varName);
   startTag.WriteXML (o);
   o << endl;
 
   WriteModelXMLFields (o); // Write the base class data fields 1st.
   if  (param)
     param->WriteXML ("Param", o);
 
   XmlTag  endTag ("ModelParamDual", XmlTag::TagTypes::tagEnd);
   endTag.WriteXML (o);
   o << endl;
 }  /* WriteXML */

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

C:/Users/Kurt/GitHub/KSquareLibraries/KKMachineLearning/ModelKnn.h
C:/Users/Kurt/GitHub/KSquareLibraries/KKMachineLearning/ModelKnn.cpp

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation