کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
417348 | 681489 | 2007 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Parallelizing AdaBoost by weights dynamics
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
AdaBoost is one of the most popular classification methods. In contrast to other ensemble methods (e.g., Bagging) the AdaBoost is inherently sequential. In many data intensive real-world situations this may limit the practical applicability of the method. P-AdaBoost is a novel scheme for the parallelization of AdaBoost, which builds upon earlier results concerning the dynamics of AdaBoost weights. P-AdaBoost yields approximations to the standard AdaBoost models that can be easily and efficiently distributed over a network of computing nodes. Properties of P-AdaBoost as a stochastic minimizer of the AdaBoost cost functional are discussed. Experiments are reported on both synthetic and benchmark data sets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 5, 1 February 2007, Pages 2487–2498
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 5, 1 February 2007, Pages 2487–2498
نویسندگان
Stefano Merler, Bruno Caprile, Cesare Furlanello,