Model clustering for neural network ensembles

被引：0
|
作者：
Bakker, B [1 ]
Heskes, T [1 ]
机构：
[1] Univ Nijmegen, SNN, NL-6525 EZ Nijmegen, Netherlands
来源：
ARTIFICIAL NEURAL NETWORKS - ICANN 2002 | 2002年 / 2415卷
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：
We show that large ensembles of (neural network) models, obtained e.g. in bootstrapping or sampling from (Bayesian) probability distributions, can be effectively summarized by a relatively small number of representative models. We present a method to find representative models through clustering based on the models' outputs on a data set. We apply the method on models obtained through bootstrapping (Boston housing) and on a multitask learning example.
引用
收藏
页码：383 / 388
页数：6
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