On combining classifiers

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On combining classifiers (1998)

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by Josef Kittler , Mohamad Hatef , Robert P. W. Duin , Jiri Matas

Venue:	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Citations:	1419 - 33 self

BibTeX

@ARTICLE{Kittler98oncombining,
    author = {Josef Kittler and Mohamad Hatef and Robert P. W. Duin and Jiri Matas},
    title = {On combining classifiers},
    journal = {IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE},
    year = {1998},
    volume = {20},
    pages = {226--239}
}

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Abstract

We develop a common theoretical framework for combining classifiers which use distinct pattern representations and show that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision. An experimental comparison of various classifier combination schemes demonstrates that the combination rule developed under the most restrictive assumptions—the sum rule—outperforms other classifier combinations schemes. A sensitivity analysis of the various schemes to estimation errors is carried out to show that this finding can be justified theoretically.

Keyphrases

combination scheme restrictive assumption sum rule common theoretical framework sensitivity analysis compound classification various scheme estimation error combination rule experimental comparison pattern representation special case distinct pattern representation

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