ITK  5.4.0
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Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Private Attributes | List of all members
itk::Statistics::MaximumRatioDecisionRule Class Reference

#include <itkMaximumRatioDecisionRule.h>

Detailed Description

A decision rule that operates as a frequentest'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 probabilities (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/Statistics/BayesianPluginClassifier.cxx, and Examples/Statistics/MaximumRatioDecisionRule.cxx.

Definition at line 59 of file itkMaximumRatioDecisionRule.h.

+ Inheritance diagram for itk::Statistics::MaximumRatioDecisionRule:
+ Collaboration diagram for itk::Statistics::MaximumRatioDecisionRule:

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

ClassIdentifierType Evaluate (const MembershipVectorType &discriminantScores) const override
const char * GetNameOfClass () const override
virtual const PriorProbabilityVectorTypeGetPriorProbabilities () 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
unsigned long AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
LightObject::Pointer CreateAnother () const override
virtual void DebugOff () const
virtual void DebugOn () const
CommandGetCommand (unsigned long tag)
bool GetDebug () const
MetaDataDictionaryGetMetaDataDictionary ()
const MetaDataDictionaryGetMetaDataDictionary () const
virtual ModifiedTimeType GetMTime () const
virtual const TimeStampGetTimeStamp () 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 noexcept override
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
Pointer Clone () const
virtual void Delete ()
virtual int GetReferenceCount () const
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 val)
- 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 &timeStamp)
 ~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

◆ ClassIdentifierType

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

Types for class identifiers.

Definition at line 80 of file itkMaximumRatioDecisionRule.h.

◆ MembershipValueType

Types for discriminant values and vectors.

Definition at line 76 of file itkMaximumRatioDecisionRule.h.

◆ MembershipVectorType

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

Definition at line 77 of file itkMaximumRatioDecisionRule.h.

◆ Pointer

Definition at line 67 of file itkMaximumRatioDecisionRule.h.

◆ PriorProbabilityValueType

Types for priors and values

Definition at line 83 of file itkMaximumRatioDecisionRule.h.

◆ PriorProbabilityVectorSizeType

Definition at line 85 of file itkMaximumRatioDecisionRule.h.

◆ PriorProbabilityVectorType

Definition at line 84 of file itkMaximumRatioDecisionRule.h.

◆ Self

Standard class type aliases

Definition at line 65 of file itkMaximumRatioDecisionRule.h.

◆ Superclass

Definition at line 66 of file itkMaximumRatioDecisionRule.h.

Constructor & Destructor Documentation

◆ MaximumRatioDecisionRule()

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

◆ ~MaximumRatioDecisionRule()

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

Member Function Documentation

◆ Evaluate()

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

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.

◆ GetNameOfClass()

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

◆ GetPriorProbabilities()

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

Get the prior probabilities.

◆ New()

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

Standard New() method support

◆ PrintSelf()

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

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.

◆ SetPriorProbabilities()

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.

Member Data Documentation

◆ m_PriorProbabilities

PriorProbabilityVectorType itk::Statistics::MaximumRatioDecisionRule::m_PriorProbabilities {}

Definition at line 114 of file itkMaximumRatioDecisionRule.h.

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