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A dynamic logistic multiple classifier system for online classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2011) 6713 LNCS 46-55
DOI: 10.1007/978-3-642-21557-5_7
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Abstract

We consider the problem of online classification in nonstationary environments. Specifically, we take a Bayesian approach to sequential parameter estimation of a logistic MCS, and compare this method with other algorithms for nonstationary classification. We comment on several design considerations. © 2011 Springer-Verlag.

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Tomas, A. (2011). A dynamic logistic multiple classifier system for online classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6713 LNCS, pp. 46–55). https://doi.org/10.1007/978-3-642-21557-5_7

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