Application of Boolean Function Complementation in Data Mining Algorithms

Grzegorz Borowik


The paper presents a method which supports three main tasks of data mining algorithms such as feature extraction, rule induction, and data discretization. It have been proved that the problems can be reduced to very efficient unate complementation algorithm. That algorithm is based on recursive execution of Shannon expansion procedure. It continues until at each leaf of the recursion tree yields the data which can be easily ccm-plemented. The fina[ result is obtained merging the results in the subtrees. According to the results of computer-based experiments this algorithm has proved very efficient.
Author Grzegorz Borowik (FEIT / IT)
Grzegorz Borowik,,
- The Institute of Telecommunications
Book Materiały konferencyjne: X Konferencja Naukowa „Informatyka – sztuka czy rzemiosło”, 2013, Warszawa, WEiT, 150 p.
Keywords in Englishfeature extraction, rale indućtion, discretization, quantIzation, data mining, Boolean function complementation, multimodal data, telecommunications, biomedical engineering.
ProjectThe Develpment of Digital Communicatios. Project leader: Lubacz Józef, , Phone: 22 234 65 31, start date 04-05-2012, planned end date 31-03-2013, end date 31-12-2013, IT/2012/statut, Completed
WEiTI Działalność statutowa
Languageen angielski
Score (nominal)0
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