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- W2377496916 abstract "Classifier selection is an effective way to design multiple classifier systems. The goal of classifier selection is to select a subset of classifiers from a given set of candidate classifiers,to achieve the best combination performance. At present,most of classifier selection methods use the stochastic search based on combination accuracy. The burden of complexity of such search limits their practical applicability for larger systems. This paper presents a new selection criterion——Improved Weighted Count of Errors and Correct Results(IWCECR) and a new heuristic search method based on IWCECR. In experiments of handwritten digit recognition,it selects a subset from 20 candidate classifiers. Results show that search efficiency of the method outperforms others and in respect of combination performance,the method also has high efficiency,although is lower than exhaust algorithm." @default.
- W2377496916 created "2016-06-24" @default.
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- W2377496916 date "2008-01-01" @default.
- W2377496916 modified "2023-09-23" @default.
- W2377496916 title "New Heuristic Classifier Selection Method" @default.
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