Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices

  • Blaise HanczarEmail author
  • Mohamed Nadif
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11051)


In many machine learning problems, the performance of the results is measured by indices that often combine precision and recall. In this paper, we study the behavior of such indices in function of the tradeoff precision-recall. We present a new tool of performance visualization and analysis referred to the tradeoff space, which plots the performance index in function of the precision-recall tradeoff. We analyse the properties of this new space and show its advantages over the precision-recall space. Code related to this paper is available at:


Evaluation Precision-recall 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.IBISCUniversity of Paris-Saclay, Univ. EvryEvryFrance
  2. 2.LIPADEUniversity of Paris DescartesParisFrance

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