Evaluation of decision table decomposition using dynamic programming classifiers

Michal Mankowski, Tadeusz Luba, Cezary Jankowski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Decision table decomposition is a method that decomposes given decision table into an equivalent set of decision tables. Decomposition can enhance the quality of knowledge discovered from databases by simplifying the data mining task. The paper contains a description of decision table decomposition method and their evaluation for data classification. Additionally, a novel method of obtaining attributes sets for decomposition was introduced. Experimental results demonstrated that decomposition can reduce memory requirements preserving the accuracy of classification.
Original languageEnglish (US)
Title of host publication24th International Workshop on Concurrency, Specification and Programming, CS and P 2015
Number of pages10
ISBN (Print)9788379961818
StatePublished - Jan 1 2015
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-30
Acknowledgements: The authors would like to thank professor Mikhail Moshkov and his team for their support while writing this paper. This research has been supported by King Abdullah University of Science and Technology.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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