ITK
4.3.0
Insight Segmentation and Registration Toolkit
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#include <itkMaximumRatioDecisionRule.h>
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 if for all class . 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 if for all class .
A priori values need to be set before calling the Evaluate method. If they are not set, a uniform prior is assumed.
Definition at line 57 of file itkMaximumRatioDecisionRule.h.
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 |
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.
typedef PriorProbabilityVectorType::size_type itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityVectorSizeType |
Definition at line 81 of file itkMaximumRatioDecisionRule.h.
typedef std::vector< PriorProbabilityValueType > itk::Statistics::MaximumRatioDecisionRule::PriorProbabilityVectorType |
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.
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Definition at line 103 of file itkMaximumRatioDecisionRule.h.
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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.
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Evaluate the decision rule . 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 .
Implements itk::Statistics::DecisionRule.
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Run-time type information (and related methods)
Reimplemented from itk::Statistics::DecisionRule.
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Get the prior probabilities.
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Standard New() method support
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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 . The likelihoods are set using the Evaluate() method. SetPriorProbabilities needs to be called before Evaluate(). If not set, assumes a uniform prior.
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private |
Definition at line 110 of file itkMaximumRatioDecisionRule.h.