Fusing Neural Networks Through Space Partitioning and Fuzzy Integration

被引：0
作者：
Antonas Verikas
Arunas Lipnickas
机构：
[1] Halmstad University,Intelligent Systems Laboratory
[2] Kaunas University of Technology,Department of Applied Electronics
来源：
Neural Processing Letters | 2002年 / 16卷
关键词：
decision fusion; fuzzy integral; Half & Half bagging; neural network;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
To improve recognition results, decisions of multiple neural networks can be aggregated into a committee decision. Aggregation weights assigned to neural networks or groups of networks can be the same in the entire data space or can be different (data dependent) in various regions of the space. In this paper, we propose a method for obtaining data dependent aggregation weights. The proposed approach is tested in two aggregation schemes, namely aggregation through neural network selection, and aggregation by the Choquet integral with respect to the λ-fuzzy measure. The effectiveness of the approach is demonstrated on two artificial and three real data sets.
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页码：53 / 65
页数：12
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