The generalization capabilities of ARTMAP

被引：0
|
作者：
Heileman, GL
Georgiopoulos, M
Healy, MJ
Verzi, SJ
机构：
来源：
1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4 | 1997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：
Bounds on the number of training examples needed to guarantee a certain level of generalization performance in the ARTMAP architecture are derived. Conditions are derived under which ARTMAP can achieve a specific level of performance assuming any unknown, but fixed, probability distribution on the training data.
引用
收藏
页码：1068 / 1071
页数：4
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