کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
534416 | 870250 | 2014 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Exploring some practical issues of SVM+: Is really privileged information that helps?
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
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چکیده انگلیسی
Learning using privileged information (LUPI) is a machine learning paradigm which aims at improving classification by taking advantage of information that is only available at training time -not at test time. SVM+ is an SVM-based implementation of LUPI. Despite this paradigm has potential interest for many applications, both LUPI and SVM+ have been scarcely explored up to date. In this work we report our effort in reproducing some results in the SVM+ literature and explore some practical issues of SVM+. The main finding is that just using randomly generated features as privileged information may perform similarly to using sensible (i.e. meaningful a priori) privileged information, at least in some problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 42, 1 June 2014, Pages 40-46
Journal: Pattern Recognition Letters - Volume 42, 1 June 2014, Pages 40-46
نویسندگان
Carlos Serra-Toro, V. Javier Traver, Filiberto Pla,