کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536515 870547 2011 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Selecting training points for one-class support vector machines
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Selecting training points for one-class support vector machines
چکیده انگلیسی

This paper proposes a training points selection method for one-class support vector machines. It exploits the feature of a trained one-class SVM, which uses points only residing on the exterior region of data distribution as support vectors. Thus, the proposed training set reduction method selects the so-called extreme points which sit on the boundary of data distribution, through local geometry and k-nearest neighbours. Experimental results demonstrate that the proposed method can reduce training set considerably, while the obtained model maintains generalization capability to the level of a model trained on the full training set, but uses less support vectors and exhibits faster training speed.


► A novel training points selection method based on local geometry and kNN is developed.
► It selects extreme points which sit on the boundary of data distribution.
► It increases training efficiency and maintains generalisation capability of 1-class SVM.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 32, Issue 11, 1 August 2011, Pages 1517–1522
نویسندگان
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