کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
407087 678126 2013 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Learning parsimonious dendritic classifiers
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Learning parsimonious dendritic classifiers
چکیده انگلیسی

From a practical industrial point of view parsimonious classifiers based on dendritic computing (DC) have two advantages: First they are implemented using only additive and min/max operators. They can be implemented in simple processors and be extremely fast providing classification responses. Second, parsimonious models improve generalization. In this paper we develop a formulation of dendritic classifiers based on lattice kernels and we train them using a direct Monte Carlo approach and a Sparse Bayesian Learning. We compare the results of both kinds of training with the relevance vector machines (RVM) on a collection of benchmark datasets.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 109, 3 June 2013, Pages 3–8
نویسندگان
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