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.
- Record ID
- Materiały konferencyjne: X Konferencja Naukowa „Informatyka – sztuka czy rzemiosło”, 2013, Warszawa, WEiT, 150 p.
- Keywords in English
- feature extraction, rale indućtion, discretization, quantIzation, data mining, Boolean function complementation, multimodal data, telecommunications, biomedical engineering.
- Project (archive)
- The Develpment of Digital Communicatios. Project leader: Lubacz Józef, +48 22 234 65 31, start date 04-05-2012, planned end date 31-03-2013, end date 31-12-2013, IT/2012/statut, CompletedWEiTIDziałalność statutowa
- (en) English
- Score (nominal)
- Uniform Resource Identifier
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or PerishOpening in a new tab system.