Investigation of expert addition criteria for dynamically changing online ensemble classifiers with multiple adaptive mechanisms
Authors: Bakirov, R. and Gabrys, B.
Journal: IFIP Advances in Information and Communication Technology
Volume: 412
Pages: 646-656
ISBN: 9783642411410
ISSN: 1868-4238
DOI: 10.1007/978-3-642-41142-7_65
Abstract:We consider online classification problem, where concepts may change over time. A prominent model for creation of dynamically changing online ensemble is used in Dynamic Weighted Majority (DWM) method. We analyse this model, and address its high sensitivity to misclassifications resulting in creation of unnecessary large ensembles, particularly while running on noisy data. We propose and evaluate various criteria for adding new experts to an ensemble.We test our algorithms on a comprehensive selection of synthetic data and establish that they lead to the significant reduction in the number of created experts and show slightly better accuracy rates than original models and non-ensemble adaptive models used for benchmarking. © IFIP International Federation for Information Processing 2013.
Source: Scopus
Investigation of Expert Addition Criteria for Dynamically Changing Online Ensemble Classifiers with Multiple Adaptive Mechanisms
Authors: Bakirov, R. and Gabrys, B.
Journal: ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2013
Volume: 412
Pages: 646-656
eISSN: 1868-422X
ISBN: 978-3-642-41142-7
ISSN: 1868-4238
Source: Web of Science (Lite)
Investigation of Expert Addition Criteria for Dynamically Changing Online Ensemble Classifiers with Multiple Adaptive Mechanisms
Authors: Bakirov, R. and Gabrys, B.
Editors: Papadopoulos, H., Andreou, A., Iliadis, L. and Maglogiannis, I.
Pages: 646-656
Publisher: Springer Berlin Heidelberg
ISBN: 978-3-642-41141-0
DOI: 10.1007/978-3-642-41142-7_65
Source: Manual
Investigation of Expert Addition Criteria for Dynamically Changing Online Ensemble Classifiers with Multiple Adaptive Mechanisms.
Authors: Bakirov, R. and Gabrys, B.
Editors: Papadopoulos, H., Andreou, A.S., Iliadis, L.S. and Maglogiannis, I.
Journal: AIAI
Volume: 412
Pages: 646-656
Publisher: Springer
ISBN: 978-3-642-41141-0
https://doi.org/10.1007/978-3-642-41142-7
Source: DBLP