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Covering Approach to Action Rule Learning

  • Paweł Matyszok
  • Marek Sikora
  • Łukasz Wróbel
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 928)

Abstract

Action rules specify recommendations which should be followed in order to transfer objects to the desired decision class. This paper presents a proposal of a novel method for induction of action rules directly from a dataset. The proposed algorithm follows the so-called covering schema and employs a pruning procedure, thus being able to produce comprehensible rule sets. An experimental study shows that the proposed method is able to discover strong actions of superior accuracy.

Notes

Acknowledgement

This work was partially supported by Polish National Centre for Research and Development (NCBiR) within the programme Prevention and Treatment of Civilization Diseases – STRATEGMED III, grant number STRATEGMED3/304586/5/NCBR/2017 (PersonALL).

A part of the work was carried out within the statutory research project of the Institute of Informatics, BK-213/RAU2/2018.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Paweł Matyszok
    • 1
  • Marek Sikora
    • 1
  • Łukasz Wróbel
    • 1
  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland

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