Artificial neural network resistance to incomplete data

被引：0
|
作者：
Tkacz, Magdalena Alicja [1 ]
机构：
[1] Univ Silesia, Inst Comp Sci, PL-41200 Sosnowiec, Poland
来源：
Intelligent Information Processing and Web Mining, Proceedings | 2006年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents results obtained in experiments related to artificial neural networks. Artificial neural networks have been trained with delta-bar-delta and conjugate gradient algorithms in case of removing some data from dataset and fulfilling empty places with mean. The goal of the experiment was to observe how long will neural network (trained with specific algorithm) be able to learn when dataset will be consistently less and less exact-the number of incomplete data is increased.
引用
收藏
页码：437 / 443
页数：7
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