کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
416024 | 681272 | 2010 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Pattern recognition via projection-based kkNN rules
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A new procedure for pattern recognition is introduced based on the concepts of random projections and nearest neighbors. It can be considered as an improvement of the classical nearest neighbor classification rules. Besides the concept of neighbors, the notion of district, a larger set into which the data will be projected, is introduced. Then a one-dimensional kkNN method is applied to the projected data on randomly selected directions. This method, which is more accurate to handle high-dimensional data, has some robustness properties. The procedure is also universally consistent. Moreover, the method is challenged with the Isolet data set where a very high classification score is obtained.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 54, Issue 5, 1 May 2010, Pages 1390–1403
Journal: Computational Statistics & Data Analysis - Volume 54, Issue 5, 1 May 2010, Pages 1390–1403
نویسندگان
Ricardo Fraiman, Ana Justel, Marcela Svarc,