A method for distributed concept drift detection
Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika, Tome 3 (2014) no. 1, pp. 113-120 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice de l'article

The paper introduces a method for distributed concept drift detection for data mining algorithms. Concept drift is understood as any unpredictable alteration in input data. There is an algorithm implementation proposed, based on MapReduce distributed computing technology. Proposed algorithm meant for concept drift detection in streaming data in online fashion. In order to provide iterative Map and Reduce phases a MapReduce framework is introduced. The algorithm is able to automatically detect input data alteration, which demands model parameters change and switching a new model online.
Keywords: concept drift, data mining, distributed computations, iterative MapRedice.
@article{VYURV_2014_3_1_a9,
     author = {A. A. Volkov and L. B\"uch and A. Andrzejak},
     title = {A method for distributed concept drift detection},
     journal = {Vestnik \^U\v{z}no-Uralʹskogo gosudarstvennogo universiteta. Seri\^a Vy\v{c}islitelʹna\^a matematika i informatika},
     pages = {113--120},
     year = {2014},
     volume = {3},
     number = {1},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VYURV_2014_3_1_a9/}
}
TY  - JOUR
AU  - A. A. Volkov
AU  - L. Büch
AU  - A. Andrzejak
TI  - A method for distributed concept drift detection
JO  - Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika
PY  - 2014
SP  - 113
EP  - 120
VL  - 3
IS  - 1
UR  - http://geodesic.mathdoc.fr/item/VYURV_2014_3_1_a9/
LA  - ru
ID  - VYURV_2014_3_1_a9
ER  - 
%0 Journal Article
%A A. A. Volkov
%A L. Büch
%A A. Andrzejak
%T A method for distributed concept drift detection
%J Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika
%D 2014
%P 113-120
%V 3
%N 1
%U http://geodesic.mathdoc.fr/item/VYURV_2014_3_1_a9/
%G ru
%F VYURV_2014_3_1_a9
A. A. Volkov; L. Büch; A. Andrzejak. A method for distributed concept drift detection. Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika, Tome 3 (2014) no. 1, pp. 113-120. http://geodesic.mathdoc.fr/item/VYURV_2014_3_1_a9/

[1] A. Andrzejak, J.B. Gomes, “Parallel Concept Drift Detection with Online Map-Reduce”, International Workshop on Knowledge Discovery (KDCloud-2012, December), 2012, 402–407

[2] M. Baena-Garc{\i}a, J. Campo-Avila, R. Fidalgo, A. Bifet, R. Gavalda, R. Morales-Bueno, “Early Drift Detection Method”, The 4th International Workshop on Knowledge Discovery from Data Streams (September, 2006), 2006, 77–86

[3] J.-H. Bose, A. Andrzejak, M. Hogqvist, “Beyond Online Aggregation: Parallel and Incremental Data Mining with Online Mapreduce”, ACM Workshop on Massive Data Analytics over the Cloud (MDAC 2010, April), 2010

[4] C. Doulkeridis, K. Nørvåg, “A Survey of Large-scale Analytical Query Processing in Mapreduce”, The VLDB Journal, 23:3, June (2014), 355–380 | DOI

[5] J. Gama, P. Medas, G. Castillo, P. Rodrigues, “Learning with Drift Detection”, Advances in Artificial Intelligence, 3171, November (2004), 286–295

[6] P. Sobhani, H. Beigy, “New Drift Detection Method for Data Streams”, Adaptive and Intelligent Systems, 6943, September (2011), 88–97