کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10361006 869957 2011 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A unifying criterion for unsupervised clustering and feature selection
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
A unifying criterion for unsupervised clustering and feature selection
چکیده انگلیسی
Exploratory data analysis methods are essential for getting insight into data. Identifying the most important variables and detecting quasi-homogenous groups of data are problems of interest in this context. Solving such problems is a difficult task, mainly due to the unsupervised nature of the underlying learning process. Unsupervised feature selection and unsupervised clustering can be successfully approached as optimization problems by means of global optimization heuristics if an appropriate objective function is considered. This paper introduces an objective function capable of efficiently guiding the search for significant features and simultaneously for the respective optimal partitions. Experiments conducted on complex synthetic data suggest that the function we propose is unbiased with respect to both the number of clusters and the number of features.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 44, Issue 4, April 2011, Pages 854-865
نویسندگان
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