Title:  A study on the performances of dynamic classifier selection based on local accuracy estimation
Internal authors: 
Issue Date:  2005
Journal: 
PATTERN RECOGNITION  
Abstract:  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
URI:  http://hdl.handle.net/11584/104925
Type: 1.1 Articolo in rivista

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