On Combining Discretisation Parameters and Attribute Ranking for Selection of Decision Rules

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10313)


The paper describes research on filtering decision rules with continuous and discretised condition attributes while combining characteristics of these attributes returned from supervised discretisation with their ranking. Numbers of intervals required for partitioning of attributes values imposed their grouping into corresponding categories, and for each group separately ranking procedures with Relief algorithm were executed. Information about numbers of bins combined with ranking positions were next exploited for selection of rules induced within rough set approaches. Filtering rules was performed directly by their conditions, or by calculating defined measures based on attribute weights, returning shortened decision algorithms with at least the same or improved classification accuracy.


Rule filtering Decision rules Continuous attributes Supervised discretisation Attribute ranking CRSA DRSA 



In the research there was used RSES system, developed at the Institute of Mathematics, Warsaw University (http://logic.mimuw.edu.pl/~rses/) [4], 4eMka Software developed at the Laboratory of Intelligent Decision Support Systems, Poznań [24], and WEKA workbench [14]. The research was performed at the Silesian University of Technology, Gliwice, within the project BK/RAu2/2017, and at the University of Silesia, Sosnowiec, within the project “Methods of artificial intelligence in information systems”.


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland
  2. 2.Institute of Computer ScienceUniversity of Silesia in KatowiceSosnowiecPoland

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