#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
typedef Superclass::ClassIdentifierType	ClassIdentifierType

typedef Superclass::MembershipValueType	MembershipValueType

typedef Superclass::MembershipVectorType	MembershipVectorType

typedef SmartPointer< Self >	Pointer

typedef MembershipValueType	PriorProbabilityValueType

typedef PriorProbabilityVectorType::size_type	PriorProbabilityVectorSizeType

typedef std::vector < PriorProbabilityValueType >	PriorProbabilityVectorType

typedef MaximumRatioDecisionRule	Self

typedef DecisionRule	Superclass

Public Types inherited from itk::Statistics::DecisionRule
typedef MembershipVectorType::size_type	ClassIdentifierType

typedef SmartPointer< const Self >	ConstPointer

typedef double	MembershipValueType

typedef std::vector < MembershipValueType >	MembershipVectorType

typedef SmartPointer< Self >	Pointer

typedef DecisionRule	Self

typedef Object	Superclass

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

typedef SmartPointer< Self >	Pointer

typedef Object	Self

typedef LightObject	Superclass

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

typedef SmartPointer< Self >	Pointer

typedef LightObject	Self

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

virtual 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

virtual void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag)

void	SetDebug (bool debugFlag) const

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

virtual void	SetReferenceCount (int) override

virtual void	UnRegister () const noexceptoverride

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 ()

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

virtual	~MaximumRatioDecisionRule () override

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

virtual	~DecisionRule () override

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

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

virtual void	SetTimeStamp (const TimeStamp &time)

virtual	~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
AtomicInt< int >	m_ReferenceCount

Member Typedef Documentation

typedef Superclass::ClassIdentifierType itk::Statistics::MaximumRatioDecisionRule::ClassIdentifierType

Types for class identifiers.

Definition at line 77 of file itkMaximumRatioDecisionRule.h.

typedef Superclass::MembershipValueType itk::Statistics::MaximumRatioDecisionRule::MembershipValueType

Types for discriminant values and vectors.

Definition at line 70 of file itkMaximumRatioDecisionRule.h.

typedef Superclass::MembershipVectorType itk::Statistics::MaximumRatioDecisionRule::MembershipVectorType

Definition at line 74 of file itkMaximumRatioDecisionRule.h.

typedef SmartPointer< Self > itk::Statistics::MaximumRatioDecisionRule::Pointer

Definition at line 64 of file itkMaximumRatioDecisionRule.h.

typedef MembershipValueType itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityValueType

Types for priors and values

Definition at line 80 of file itkMaximumRatioDecisionRule.h.

typedef PriorProbabilityVectorType::size_type itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityVectorSizeType

Definition at line 82 of file itkMaximumRatioDecisionRule.h.

typedef std::vector< PriorProbabilityValueType > itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityVectorType

Definition at line 81 of file itkMaximumRatioDecisionRule.h.

typedef MaximumRatioDecisionRule itk::Statistics::MaximumRatioDecisionRule::Self

Standard class typedefs

Definition at line 62 of file itkMaximumRatioDecisionRule.h.

typedef DecisionRule itk::Statistics::MaximumRatioDecisionRule::Superclass

Definition at line 63 of file itkMaximumRatioDecisionRule.h.

Constructor & Destructor Documentation

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

protected

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

inlineoverrideprotectedvirtual

Definition at line 104 of file itkMaximumRatioDecisionRule.h.

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.

virtual 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

virtual 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.