ITK  4.3.0
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itk::Statistics::MaximumRatioDecisionRule Class Reference

#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

Definition at line 57 of file itkMaximumRatioDecisionRule.h.

Public Types

typedef
Superclass::ClassIdentifierType 
ClassIdentifierType
 
typedef
Superclass::MembershipValueType 
MembershipValueType
 
typedef
Superclass::MembershipVectorType 
MembershipVectorType
 
typedef SmartPointer< SelfPointer
 
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 SelfConstPointer
 
typedef double MembershipValueType
 
typedef std::vector
< MembershipValueType
MembershipVectorType
 
typedef SmartPointer< SelfPointer
 
typedef DecisionRule Self
 
typedef Object Superclass
 
- Public Types inherited from itk::Object
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef Object Self
 
typedef LightObject Superclass
 
- Public Types inherited from itk::LightObject
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef LightObject Self
 

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother (void) const
 
virtual ClassIdentifierType Evaluate (const MembershipVectorType &discriminantScores) const
 
virtual const char * GetNameOfClass () const
 
virtual const
PriorProbabilityVectorType
GetPriorProbabilities ()
 
void SetPriorProbabilities (const PriorProbabilityVectorType &p)
 

Static Public Member Functions

static Pointer New ()
 

Protected Member Functions

 MaximumRatioDecisionRule ()
 
void PrintSelf (std::ostream &os, Indent indent) const
 
virtual ~MaximumRatioDecisionRule ()
 
- Protected Member Functions inherited from itk::Statistics::DecisionRule
 DecisionRule ()
 
virtual ~DecisionRule ()
 
- Protected Member Functions inherited from itk::Object
 Object ()
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
virtual ~Object ()
 
- 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 Member Functions

 MaximumRatioDecisionRule (const Self &)
 
void operator= (const Self &)
 

Private Attributes

PriorProbabilityVectorType m_PriorProbabilities
 

Additional Inherited Members

- Protected Types inherited from itk::LightObject
typedef int InternalReferenceCountType
 
- Protected Attributes inherited from itk::LightObject
InternalReferenceCountType m_ReferenceCount
 
SimpleFastMutexLock m_ReferenceCountLock
 

Member Typedef Documentation

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

Types for class identifiers.

Definition at line 76 of file itkMaximumRatioDecisionRule.h.

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

Types for discriminant values and vectors.

Definition at line 69 of file itkMaximumRatioDecisionRule.h.

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

Definition at line 73 of file itkMaximumRatioDecisionRule.h.

Definition at line 63 of file itkMaximumRatioDecisionRule.h.

Types for priors and values

Definition at line 79 of file itkMaximumRatioDecisionRule.h.

Definition at line 81 of file itkMaximumRatioDecisionRule.h.

Definition at line 80 of file itkMaximumRatioDecisionRule.h.

Standard class typedefs

Definition at line 61 of file itkMaximumRatioDecisionRule.h.

Definition at line 62 of file itkMaximumRatioDecisionRule.h.

Constructor & Destructor Documentation

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

Definition at line 103 of file itkMaximumRatioDecisionRule.h.

itk::Statistics::MaximumRatioDecisionRule::MaximumRatioDecisionRule ( const Self )
private

Member Function Documentation

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

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 ( )
virtual

Get the prior probabilities.

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

Standard New() method support

void itk::Statistics::MaximumRatioDecisionRule::operator= ( const Self )
private
void itk::Statistics::MaximumRatioDecisionRule::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
protectedvirtual

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.

Member Data Documentation

PriorProbabilityVectorType itk::Statistics::MaximumRatioDecisionRule::m_PriorProbabilities
private

Definition at line 110 of file itkMaximumRatioDecisionRule.h.


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