کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
530615 869779 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
InstanceRank based on borders for instance selection
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
InstanceRank based on borders for instance selection
چکیده انگلیسی

Instance selection algorithms are used for reducing the number of training instances. However, most of them suffer from long runtimes which results in the incapability to be used with large datasets. In this work, we introduce an Instance Ranking per class using Borders (instances near to instances belonging to different classes), using this ranking we propose an instance selection algorithm (IRB). We evaluated the proposed algorithm using k-NN with small and large datasets, comparing it against state of the art instance selection algorithms. In our experiments, for large datasets IRB has the best compromise between time and accuracy. We also tested our algorithm using SVM, LWLR and C4.5 classifiers, in all cases the selection computed by our algorithm obtained the best accuracies in average.


► Most of the instance selection algorithms suffer from long runtimes.
► We introduce an Instance Ranking per class using border class instances.
► Using this ranking we propose IRB, an instance selection algorithm.
► For large datasets IRB obtains the best compromise between time and accuracy.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 46, Issue 1, January 2013, Pages 365–375
نویسندگان
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