کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
415690 681226 2013 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Clustering through empirical likelihood ratio
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Clustering through empirical likelihood ratio
چکیده انگلیسی

There is a vast variety of clustering methods available in the literature. The performance of many of them strongly depends on specific patterns in data. This paper introduces a clustering procedure based on the empirical likelihood method which inherits many advantages of the classical likelihood approach without imposing restrictive probability distribution constraints. The performance of the proposed procedure is illustrated on simulated and classification datasets with excellent results. The comparison of the algorithm with several well-known clustering methods is very encouraging. The procedure is more robust and has higher accuracy than the competitors.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 62, June 2013, Pages 1–10
نویسندگان
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