کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
406521 678092 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nearest convex hull classification by using Lotka–Volterra recurrent neural networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Nearest convex hull classification by using Lotka–Volterra recurrent neural networks
چکیده انگلیسی

Distance-based classifiers have been applied to many multi-class classification problems. The nearest convex hull classifier (NCHC) is a useful distance-based classifier. It assigns a test sample to the class that has the closest convex hull. This paper proposes a new algorithm to implement the NCHC. Considering an alternative interpretation of NCHC, the distance from the test sample to the convex hull of the training data in a certain class can be thought of as the reconstruction error. We propose an algorithm that uses neural networks to implement the NCHC. Our experimental results show that NCHC using Lotka–Volterra recurrent neural networks outperforms other classifiers in a whole.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 138, 22 August 2014, Pages 157–166
نویسندگان
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