%0 Conference Proceedings
%T Ensembles of Heterogeneous Concept Drift Detectors - Experimental Study
%+ Wroclaw University of Science and Technology
%+ AGH University of Science and Technology [Krakow, PL] (AGH UST)
%A Woźniak, Michał
%A Ksieniewicz, Paweł
%A Cyganek, Bogusław
%A Walkowiak, Krzysztof
%Z Part 7: Decisions
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Vilnius, Lithuania
%Y Khalid Saeed
%Y Władysław Homenda
%I Springer International Publishing
%3 Computer Information Systems and Industrial Management
%V LNCS-9842
%P 538-549
%8 2016-09-14
%D 2016
%R 10.1007/978-3-319-45378-1_48
%K Data stream
%K Concept drift
%K Pattern classification
%K Drift detector
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X For the contemporary enterprises, possibility of appropriate business decision making on the basis of the knowledge hidden in stored data is the critical success factor. Therefore, the decision support software should take into consideration that data usually comes continuously in the form of so-called data stream, but most of the traditional data analysis methods are not ready to efficiently analyze fast growing amount of the stored records. Additionally, one should also consider phenomenon appearing in data stream called concept drift, which means that the parameters of an using model are changing, what could dramatically decrease the analytical model quality. This work is focusing on the classification task, which is very popular in many practical cases as fraud detection, network security, or medical diagnosis. We propose how to detect the changes in the data stream using combined concept drift detection model. The experimental evaluations confirm its pretty good quality, what encourage us to use it in practical applications.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01637510/document
%2 https://inria.hal.science/hal-01637510/file/419526_1_En_48_Chapter.pdf
%L hal-01637510
%U https://inria.hal.science/hal-01637510
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-CISIM
%~ IFIP-LNCS-9842