Class computing the confusion matrix given two vectors of integer. More...

#include <STK_Stat_ConfusionMatrix.h>

Public Member Functions
	ConfusionMatrix (TrueArray const &trueClass, PredArray const &predictClass)
	default constructor

CSquareXi	operator() ()

Protected Attributes
TrueArray const &	trueClass_

PredArray const &	predictClass_

Detailed Description

template<class TrueArray, class PredArray>
class STK::Stat::ConfusionMatrix< TrueArray, PredArray >

Class computing the confusion matrix given two vectors of integer.

Definition at line 50 of file STK_Stat_ConfusionMatrix.h.

Constructor & Destructor Documentation

◆ ConfusionMatrix()

template<class TrueArray , class PredArray >

STK::Stat::ConfusionMatrix< TrueArray, PredArray >::ConfusionMatrix	(	TrueArray const &	trueClass,
		PredArray const &	predictClass
	)

inline

default constructor

Definition at line 54 of file STK_Stat_ConfusionMatrix.h.

                   : trueClass_(trueClass), predictClass_(predictClass)
    {
      STK_STATIC_ASSERT_ONE_DIMENSION_ONLY(TrueArray);
      STK_STATIC_ASSERT_ONE_DIMENSION_ONLY(PredArray);
      if (trueClass_.range() != predictClass_.range())
      { STKRUNTIME_ERROR_NO_ARG(confusionMatrix(trueClass,predictClass),trueClass and predictClass are not of the same size);}
    }

References STK::Stat::confusionMatrix(), STK::Stat::ConfusionMatrix< TrueArray, PredArray >::predictClass_, STK_STATIC_ASSERT_ONE_DIMENSION_ONLY, STKRUNTIME_ERROR_NO_ARG, and STK::Stat::ConfusionMatrix< TrueArray, PredArray >::trueClass_.

Member Function Documentation

◆ operator()()

template<class TrueArray , class PredArray >

CSquareXi STK::Stat::ConfusionMatrix< TrueArray, PredArray >::operator() ( )

inline

Returns: the confusion matrix obtained with the true classes and the predicted classes.

Definition at line 66 of file STK_Stat_ConfusionMatrix.h.

    {
      // compute nbLevels and create result
      int min = std::min(trueClass_.minElt(), predictClass_.minElt());
      int max = std::max(trueClass_.maxElt(), predictClass_.maxElt());
      CSquareXi res(Range(min, max, 0), 0);
      for (int i=trueClass_.begin(); i<trueClass_.end(); ++i)
      { res(trueClass_[i], predictClass_[i])++;}
      return res;
    }