/usr/include/InsightToolkit/Review/Statistics/itkMaximumRatioDecisionRule2.h is in libinsighttoolkit3-dev 3.20.1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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Program: Insight Segmentation & Registration Toolkit
Module: itkMaximumRatioDecisionRule2.h
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkMaximumRatioDecisionRule2_h
#define __itkMaximumRatioDecisionRule2_h
#include <vector>
#include "vnl/vnl_matrix.h"
#include "itkNumericTraits.h"
#include "itkDecisionRule.h"
namespace itk {
namespace Statistics {
/** \class MaximumRatioDecisionRule2
* \brief This rule returns \f$i\f$ if
* \f$\frac{f_{i}(\overrightarrow{x})}{f_{j}(\overrightarrow{x})} >
* \frac{K_{j}}{K_{i}}\f$ for all \f$j \not= i\f$,
* where the \f$i\f$ is the index of a class which has
* membership function \f$f_{i}\f$ and its prior value
* (usually, the a priori probability or the size of a class) is
* \f$K_{i}\f$
*
* Users should set the a priori values before calling the Evaluate method.
*
* \sa MaximumDecisionRule, MinimumDecisionRule
*/
class ITK_EXPORT MaximumRatioDecisionRule2 :
public DecisionRule
{
public:
/** Standard class typedefs */
typedef MaximumRatioDecisionRule2 Self;
typedef DecisionRule Superclass;
typedef SmartPointer<Self> Pointer;
/** Run-time type information (and related methods) */
itkTypeMacro(MaximumRatioDecisionRule2, DecisionRule);
/** Standard New() method support */
itkNewMacro(Self);
typedef float APrioriValueType;
typedef std::vector< APrioriValueType > APrioriVectorType;
typedef APrioriVectorType::size_type APrioriVectorSizeType;
typedef Superclass::MembershipVectorType MembershipVectorType;
/** The return value of this function is a class label.
* Basically, using its internal logic based on the discriminant
* scores, this function decides best class label and return it.
*/
virtual unsigned int Evaluate( const MembershipVectorType &discriminantScores) const;
/** Sets the a priori probabilities */
void SetAPriori(APrioriVectorType& values);
protected:
MaximumRatioDecisionRule2();
virtual ~MaximumRatioDecisionRule2() {}
private:
MaximumRatioDecisionRule2(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
/** Number of classes */
APrioriVectorSizeType m_NumberOfClasses;
/** a priori probability ratio matrix: internal use */
vnl_matrix< double > m_APrioriRatioMatrix;
}; // end of class
} // end of Statistics namespace
} // end of ITK namespace
#endif
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