A Bayesian boosting theorem
نویسندگان
چکیده
We re®ne the ®rst theorem of (R. bounding the error of the ADA DABOOST OOST boosting algorithm, to integrate Bayes risk. This suggests the signi®cant time savings could be obtained on some domains without damaging the solution. An applicative example is given in the ®eld of feature selection.
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ورودعنوان ژورنال:
- Pattern Recognition Letters
دوره 22 شماره
صفحات -
تاریخ انتشار 2001