کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
534493 | 870257 | 2015 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fast data selection for SVM training using ensemble margin
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Support Vector Machine (SVM) is a powerful classification method. However, it suffers a major drawback: the high memory and time complexity of the training which constrains the application of SVM to large size classification tasks. To accelerate the SVM training, a new ensemble margin-based data selection approach is proposed. It relies on a simple and efficient heuristic to provide support vector candidates: selecting lowest margin instances. This technique significantly reduces the SVM training task complexity while maintaining the accuracy of the SVM classification. A fast alternative of our approach we called SVIS (Small Votes Instance Selection) with great potential for large data problem is also introduced.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 51, 1 January 2015, Pages 112–119
Journal: Pattern Recognition Letters - Volume 51, 1 January 2015, Pages 112–119
نویسندگان
Li Guo, Samia Boukir,