Discretized-Vapnik-Chervonenkis dimension for analyzing complexity of real function classes

• المؤلفون الرئيسيون: Zhang, Chao, Bian, Wei, Tao, Dacheng, Lin, Weisi
• مؤلفون آخرون: School of Computer Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2013
• الموضوعات: DRNTU::Engineering::Computer science and engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/99545; http://hdl.handle.net/10220/13524

In this paper, we introduce the discretized-Vapnik-Chervonenkis (VC) dimension for studying the complexity of a real function class, and then analyze properties of real function classes and neural networks. We first prove that a countable traversal set is enough to achieve the VC dimension for a rea...