#include <itkMaximumRatioDecisionRule.h>

Inheritance diagram for itk::Statistics::MaximumRatioDecisionRule:

Collaboration diagram for itk::Statistics::MaximumRatioDecisionRule:

Detailed Description

A decision rule that operates as a frequentist's approximation to Bayes rule.

MaximumRatioDecisionRule returns the class label using a Bayesian style decision rule. The discriminant scores are evaluated in the context of class priors. If the discriminant scores are actual conditional probabilites (likelihoods) and the class priors are actual a priori class probabilities, then this decision rule operates as Bayes rule, returning the class $i$ if $p(x|i) p(i) > p(x|j) p(j)$ for all class $j$ . The discriminant scores and priors are not required to be true probabilities.

This class is named the MaximumRatioDecisionRule as it can be implemented as returning the class $i$ if $\frac{p(x|i)}{p(x|j)} > \frac{p(j)}{p(i)}$ for all class $j$ .

A priori values need to be set before calling the Evaluate method. If they are not set, a uniform prior is assumed.

See Also: MaximumDecisionRule, MinimumDecisionRule

Examples:: Examples/Statistics/BayesianPluginClassifier.cxx, and Examples/Statistics/MaximumRatioDecisionRule.cxx.

Definition at line 58 of file itkMaximumRatioDecisionRule.h.

Public Types
using	ClassIdentifierType = Superclass::ClassIdentifierType

using	MembershipValueType = Superclass::MembershipValueType

using	MembershipVectorType = Superclass::MembershipVectorType

using	Pointer = SmartPointer< Self >

using	PriorProbabilityValueType = MembershipValueType

using	PriorProbabilityVectorSizeType = PriorProbabilityVectorType::size_type

using	PriorProbabilityVectorType = std::vector< PriorProbabilityValueType >

using	Self = MaximumRatioDecisionRule

using	Superclass = DecisionRule

Public Types inherited from itk::Statistics::DecisionRule
using	ClassIdentifierType = MembershipVectorType::size_type

using	ConstPointer = SmartPointer< const Self >

using	MembershipValueType = double

using	MembershipVectorType = std::vector< MembershipValueType >

using	Pointer = SmartPointer< Self >

using	Self = DecisionRule

using	Superclass = Object

Public Types inherited from itk::Object
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = Object

using	Superclass = LightObject

Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = LightObject

Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother () const

ClassIdentifierType	Evaluate (const MembershipVectorType &discriminantScores) const override

virtual const char *	GetNameOfClass () const

virtual const PriorProbabilityVectorType &	GetPriorProbabilities () const

void	SetPriorProbabilities (const PriorProbabilityVectorType &p)

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)

unsigned long	AddObserver (const EventObject &event, Command *) const

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

virtual const TimeStamp &	GetTimeStamp () const

bool	HasObserver (const EventObject &event) const

void	InvokeEvent (const EventObject &)

void	InvokeEvent (const EventObject &) const

virtual void	Modified () const

void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag)

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexceptoverride

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
virtual void	Delete ()

virtual int	GetReferenceCount () const

	itkCloneMacro (Self)

void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions
static Pointer	New ()

Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()

static void	GlobalWarningDisplayOff ()

static void	GlobalWarningDisplayOn ()

static Pointer	New ()

static void	SetGlobalWarningDisplay (bool flag)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

Protected Member Functions
	MaximumRatioDecisionRule ()

void	PrintSelf (std::ostream &os, Indent indent) const override

	~MaximumRatioDecisionRule () override=default

Protected Member Functions inherited from itk::Statistics::DecisionRule
	DecisionRule ()

	~DecisionRule () override

Protected Member Functions inherited from itk::Object
	Object ()

bool	PrintObservers (std::ostream &os, Indent indent) const

virtual void	SetTimeStamp (const TimeStamp &time)

	~Object () override

Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const

	LightObject ()

virtual void	PrintHeader (std::ostream &os, Indent indent) const

virtual void	PrintTrailer (std::ostream &os, Indent indent) const

virtual	~LightObject ()

Private Attributes
PriorProbabilityVectorType	m_PriorProbabilities

Additional Inherited Members
Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount

Member Typedef Documentation

using itk::Statistics::MaximumRatioDecisionRule::ClassIdentifierType = Superclass::ClassIdentifierType

Types for class identifiers.

Definition at line 79 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::MembershipValueType = Superclass::MembershipValueType

Types for discriminant values and vectors.

Definition at line 75 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::MembershipVectorType = Superclass::MembershipVectorType

Definition at line 76 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::Pointer = SmartPointer< Self >

Definition at line 66 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityValueType = MembershipValueType

Types for priors and values

Definition at line 82 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityVectorSizeType = PriorProbabilityVectorType::size_type

Definition at line 84 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityVectorType = std::vector< PriorProbabilityValueType >

Definition at line 83 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::Self = MaximumRatioDecisionRule

Standard class type aliases

Definition at line 64 of file itkMaximumRatioDecisionRule.h.

using itk::Statistics::MaximumRatioDecisionRule::Superclass = DecisionRule

Definition at line 65 of file itkMaximumRatioDecisionRule.h.

Constructor & Destructor Documentation

itk::Statistics::MaximumRatioDecisionRule::MaximumRatioDecisionRule ( )

protected

itk::Statistics::MaximumRatioDecisionRule::~MaximumRatioDecisionRule ( )

overrideprotecteddefault

Member Function Documentation

virtual::itk::LightObject::Pointer itk::Statistics::MaximumRatioDecisionRule::CreateAnother ( ) const

virtual

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Object.

ClassIdentifierType itk::Statistics::MaximumRatioDecisionRule::Evaluate ( const MembershipVectorType & discriminantScores ) const

overridevirtual

Evaluate the decision rule $p(x|i) p(i) > p(x|j) p(j)$ . Prior probabilities need to be set before calling Evaluate() using the SetPriorProbabilities() method (otherwise a uniform prior is assumed). Parameter to Evaluate() is the discriminant score in the form of a likelihood $p(x|i)$ .

Implements itk::Statistics::DecisionRule.

virtual const char* itk::Statistics::MaximumRatioDecisionRule::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods)

Reimplemented from itk::Statistics::DecisionRule.

virtual const PriorProbabilityVectorType& itk::Statistics::MaximumRatioDecisionRule::GetPriorProbabilities ( ) const

virtual

Get the prior probabilities.

static Pointer itk::Statistics::MaximumRatioDecisionRule::New ( )

static

Standard New() method support

void itk::Statistics::MaximumRatioDecisionRule::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

overrideprotectedvirtual

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::Object.

void itk::Statistics::MaximumRatioDecisionRule::SetPriorProbabilities ( const PriorProbabilityVectorType & p )

Set the prior probabilities used in evaluating $p(x|i) p(i) > p(x|j) p(j)$ . The likelihoods are set using the Evaluate() method. SetPriorProbabilities needs to be called before Evaluate(). If not set, assumes a uniform prior.