Combining Models in Classification and Pattern Pecognition
عنوان مقاله: Combining Models in Classification and Pattern Pecognition
شناسه ملی مقاله: ISC05_013
منتشر شده در پنجمین کنفرانس آمار ایران در سال 1379
شناسه ملی مقاله: ISC05_013
منتشر شده در پنجمین کنفرانس آمار ایران در سال 1379
مشخصات نویسندگان مقاله:
Majid Mojirsheibani - This research was supported in part by a grant from NSERC Canada. Scholl of Mathematics & Statistics, Carleton University, Ottawa, Ontario, KIS ۵B۶ Canada.
خلاصه مقاله:
Majid Mojirsheibani - This research was supported in part by a grant from NSERC Canada. Scholl of Mathematics & Statistics, Carleton University, Ottawa, Ontario, KIS ۵B۶ Canada.
Data-based procedures are proposed for combining a number of individual classifiers in order to construct more effective classification rules. The resulting combined classifiers turn out to be almost surely superior to each individual classifier, under appropriate regularity conditions. Here, superiority means lower asymptotic misclassification error rate. Both the mechanics and the asymptotic validity of the proposed procedures are discussed.
کلمات کلیدی: Classification, Bayes classifier, consistency.
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/84763/