期刊
PATTERN RECOGNITION
卷 38, 期 11, 页码 2188-2191出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2005.02.010
关键词
multiple classifier systems; dynamic classifier selection; performance evaluation
Dynamic classifier selection (DCS) plays a strategic role in the field of multiple classifier systems (MCS). This paper proposes a study on the performances of DCS by Local Accuracy estimation (DCS-LA). To this end, upper bounds against which the performances can be evaluated are proposed. The experimental results on five datasets clearly show the effectiveness of the selection methods based on local accuracy estimates. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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