کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
409637 679080 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The imprecise Dirichlet model as a basis for a new boosting classification algorithm
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
The imprecise Dirichlet model as a basis for a new boosting classification algorithm
چکیده انگلیسی

A new algorithm for ensemble construction based on adapted restricting a set of weights of examples in training data to avoid overfitting and to reduce a number of iterations is proposed in the paper. The algorithm called IDMBoost (Imprecise Dirichlet Model Boost) applies Walley׳s imprecise Dirichlet model for modifying the restricted sets of weights depending on the number and location of classification errors. Updating of weights within the restricted set (simplex) is carried out by using its extreme points. The proposed algorithm has a double adaptation procedure. The first adaptation is carried out within every restricted simplex like the AdaBoost. The second adaptation reduces and changes the restricted sets of possible weights of examples. Various numerical experiments with real data illustrate the proposed algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 151, Part 3, 3 March 2015, Pages 1374–1383
نویسندگان
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