TY - GEN
T1 - Detecting changes in qualitative data streams
AU - Ienco, Dino
AU - Bifet, Albert
AU - Pfahringer, Bernhard
AU - Poncelet, Pascal
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In real world applications, data streams have categorical features, and changes induced in the data distribution of these categorical features have not been considered extensively so far. Previous work focused on detecting changes in the accuracy of the learners, but without considering changes in the data distribution. To cope with these issues, we propose a new unsupervised change detection method well suited for categorical data streams.
AB - In real world applications, data streams have categorical features, and changes induced in the data distribution of these categorical features have not been considered extensively so far. Previous work focused on detecting changes in the accuracy of the learners, but without considering changes in the data distribution. To cope with these issues, we propose a new unsupervised change detection method well suited for categorical data streams.
M3 - Conference contribution
AN - SCOPUS:84994301835
T3 - Revue des Nouvelles Technologies de l'Information
SP - 517
EP - 520
BT - Extraction et Gestion des Connaissances, EGC 2014
PB - Hermann-Editions
T2 - 14e Journees Internationales Francophones sur l'Extraction et la Gestion des Connaissances, EGC 2014 - 14th International French-Speaking Conference on Knowledge Extraction and Management, EGC 2014
Y2 - 28 January 2014 through 31 January 2014
ER -