ITK  4.9.0
Insight Segmentation and Registration Toolkit
Examples/Statistics/MaximumDecisionRule.cxx
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*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
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*
* http://www.apache.org/licenses/LICENSE-2.0.txt
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// Software Guide : BeginLatex
//
// \index{itk::Statistics::Maximum\-Decision\-Rule}
//
// The \doxygen{MaximumDecisionRule} returns the index of the largest
// discriminant score among the discriminant scores in the vector of
// discriminant scores that is the input argument of the \code{Evaluate()}
// method.
//
// To begin the example, we include the header files for the class and the
// MaximumDecisionRule. We also include the header file for the
// \code{std::vector} class that will be the container for the discriminant
// scores.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include <vector>
// Software Guide : EndCodeSnippet
int main(int, char*[])
{
// Software Guide : BeginLatex
//
// The instantiation of the function is done through the usual
// \code{New()} method and a smart pointer.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::Statistics::MaximumDecisionRule DecisionRuleType;
DecisionRuleType::Pointer decisionRule = DecisionRuleType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We create the discriminant score vector and fill it with three
// values. The \code{Evaluate( discriminantScores )} will return 2
// because the third value is the largest value.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
DecisionRuleType::MembershipVectorType discriminantScores;
discriminantScores.push_back( 0.1 );
discriminantScores.push_back( 0.3 );
discriminantScores.push_back( 0.6 );
std::cout << "MaximumDecisionRule: The index of the chosen = "
<< decisionRule->Evaluate( discriminantScores )
<< std::endl;
// Software Guide : EndCodeSnippet
return EXIT_SUCCESS;
}