کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1144867 1489625 2011 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A weight-adjusted voting algorithm for ensembles of classifiers
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آمار و احتمال
پیش نمایش صفحه اول مقاله
A weight-adjusted voting algorithm for ensembles of classifiers
چکیده انگلیسی

We present a new weighted voting classification ensemble method, called WAVE, that uses two weight vectors: a weight vector of classifiers and a weight vector of instances. The instance weight vector assigns higher weights to observations that are hard to classify. The weight vector of classifiers puts larger weights on classifiers that perform better on hard-to-classify instances. One weight vector is designed to be calculated in conjunction with the other through an iterative procedure. That is, the instances of higher weights play a more important role in determining the weights of classifiers, and vice versa. We proved that the iterated weight vectors converge to the optimal weights which can be directly calculated from the performance matrix of classifiers in an ensemble. The final prediction of the ensemble is obtained by voting using the optimal weight vector of classifiers. To compare the performance between a simple majority voting and the proposed weighted voting, we applied both of the voting methods to bootstrap aggregation and investigated the performance on 28 datasets. The result shows that the proposed weighted voting performs significantly better than the simple majority voting in general.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of the Korean Statistical Society - Volume 40, Issue 4, December 2011, Pages 437–449
نویسندگان
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