Metric Logic Program Explanations for Complex Separator Functions

  • Srijan Kumar
  • Edoardo Serra
  • Francesca SpezzanoEmail author
  • V. S. Subrahmanian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9858)


There are many classifiers that treat entities to be classified as points in a high-dimensional vector space and then compute a separator S between entities in class \(+1\) from those in class \(-1\). However, such classifiers are usually very hard to explain in plain English to domain experts. We propose Metric Logic Programs (MLPs) which are a fragment of constraint logic programs as a new paradigm for explaining S. We present multiple measures of quality of an MLP and define the problem of finding an MLP-Explanation of S and show that it - and various related problems - are NP-hard. We present the MLP_Extract algorithm to extract MLP explanations for S. We show that while our algorithms provide more succinct, simpler, and higher fidelity explanations than association rules that are less expressive, our algorithms do require additional run-time.


Support Vector Machine Association Rule Logic Program Past Work Predicate Symbol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Parts of this work were supported by ONR grant N000141612739 and ARO grant W911NF1610342.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Srijan Kumar
    • 1
  • Edoardo Serra
    • 2
  • Francesca Spezzano
    • 2
    Email author
  • V. S. Subrahmanian
    • 1
  1. 1.Computer Science DepartmentUniversity of MarylandCollege ParkUSA
  2. 2.Computer Science DepartmentBoise State UniversityBoiseUSA

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