Decision Rule Learning for Evolving Data Streams – RNDr. Petr Kosina, Ph.D.
RNDr. Petr Kosina, Ph.D.
Doctoral thesis
Decision Rule Learning for Evolving Data Streams
Decision Rule Learning for Evolving Data Streams
Abstract:
V této práci je navržen ucelený systém pro učení rozhodovacích pravidel z proudů dat a jeho aplikace v oblastech klasifikace v proudech dat a on-line rozpoznávání anomálií v datech. Dolování z proudů dat je proces, při nemž jsou extrahovány znalosti z rychle a nepřetržitě přicházejících záznamů. Na velké množství úloh dolování z dat v dnešní době lze pohlížet jako na dolování z proudů dat, proto se …moreAbstract:
This dissertation proposes a complex approach for learning decision rules from data streams and their application in classification and anomaly detection. Data Stream Mining is the process of extracting knowledge structures from continuous and rapidly incoming data records. Many decision tasks can be formulated as stream mining problems and therefore many new algorithms for data streams have been proposed …more
Language used: English
Date on which the thesis was submitted / produced: 19. 8. 2013
Identifier:
https://is.muni.cz/th/u1v05/
Thesis defence
- Date of defence: 20. 12. 2013
- Supervisor: doc. RNDr. Lubomír Popelínský, Ph.D., Assoc. Prof. Joao Gama
- Reader: Prof. Dr. Myra Spiliopoulou, Assist. Prof. Mykola Pechenizkiy, Dr. Albert Bifet
Citation record
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsDoctoral programme / field:
Informatics (4-years) / Informatics
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