کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536901 870642 2006 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Partition based pattern synthesis technique with efficient algorithms for nearest neighbor classification
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Partition based pattern synthesis technique with efficient algorithms for nearest neighbor classification
چکیده انگلیسی

Nearest neighbor (NN) classifier is a popular non-parametric classifier. It is conceptually a simple classifier and shows good performance. Due to the curse of dimensionality effect, the size of training set needed by it to achieve a given classification accuracy becomes prohibitively large when the dimensionality of the data is high. Generating artificial patterns can reduce this effect. In this paper, we propose a novel pattern synthesis method called partition based pattern synthesis which can generate an artificial training set of exponential order when compared with that of the given original training set. We also propose suitable faster NN based methods to work with the synthetic training patterns. Theoretically, the relationship between our methods and conventional NN methods is established. The computational requirements of our methods are also theoretically established. Experimental results show that NN based classifiers with synthetic training set can outperform conventional NN classifiers and some other related classifiers.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 27, Issue 14, 15 October 2006, Pages 1714–1724
نویسندگان
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