Optimization of Inhibitory Decision Rules Relative to Length and Coverage

The paper is devoted to the study of algorithms for optimization of inhibitory rules relative to the length and coverage. In contrast with usual rules that have on the right-hand side a relation "attribute = value", inhibitory rules have a relation "attribute ≠ value" on the right-hand side. The considered algorithms are based on extensions of dynamic programming.

[1]  Andrzej Skowron,et al.  Inhibitory Rules in Data Analysis: A Rough Set Approach , 2009, Studies in Computational Intelligence.

[2]  Igor Chikalov,et al.  Dynamic Programming Algorithm for Optimization of β-Decision Rules , 2011 .

[3]  Andrzej Skowron,et al.  Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam - Volume 2 , 2013, Rough Sets and Intelligent Systems.

[4]  Zbigniew Suraj,et al.  Some Remarks on Extensions and Restrictions of Information Systems , 2000, Rough Sets and Current Trends in Computing.

[5]  Andrzej Skowron,et al.  Comparison of Lazy Classification Algorithms Based on Deterministic and Inhibitory Decision Rules , 2008, RSKT.

[6]  Guoyin Wang,et al.  Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing , 2013, Lecture Notes in Computer Science.

[7]  Andrzej Skowron,et al.  Rough sets and concurrency , 1993 .

[8]  Mikhail Ju. Moshkov,et al.  Combinatorial Machine Learning - A Rough Set Approach , 2011, Studies in Computational Intelligence.

[9]  Igor Chikalov,et al.  Dynamic programming approach to optimization of approximate decision rules , 2013, Inf. Sci..

[10]  Igor Chikalov,et al.  Dynamic Programming Approach for Exact Decision Rule Optimization , 2013, Rough Sets and Intelligent Systems.

[11]  J. Rissanen,et al.  Modeling By Shortest Data Description* , 1978, Autom..

[12]  Andrzej Skowron,et al.  Two Families of Classification Algorithms , 2007, RSFDGrC.

[13]  Andrzej Skowron,et al.  Lazy Classification Algorithms Based on Deterministic and Inhibitory Rules , 2008 .