کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536205 870480 2006 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Ho–Kashyap classifier with early stopping for regularization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Ho–Kashyap classifier with early stopping for regularization
چکیده انگلیسی

This paper focuses on linear classification using a fast and simple algorithm known as the Ho–Kashyap learning rule (HK). In order to avoid overfitting and instead of adding a regularization parameter in the criterion, early stopping is introduced as a regularization method for HK learning, which becomes HKES (Ho–Kashyap with early stopping). Furthermore, an automatic procedure, based on the generalization error estimation, is proposed to tune the stopping time. The method is then tested and compared to others (including SVM and LSVM), that use either ℓ1 or ℓ2-norm of the errors, on well-known benchmarks. The results show the limits of early stopping for regularization with respect to the generalization error estimation and the drawbacks of low level hyperparameters such as a number of iterations.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 27, Issue 9, 1 July 2006, Pages 1037–1044
نویسندگان
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