Fusing neural networks through space partitioning and fuzzy integration

被引:25
作者
Verikas, A
Lipnickas, A
机构
[1] Halmstad Univ, Intelligent Syst Lab, S-30118 Halmstad, Sweden
[2] Kaunas Univ Technol, Dept Appl Elect, LT-3031 Kaunas, Lithuania
关键词
decision fusion; fuzzy integral; Half & Half bagging; neural network;
D O I
10.1023/A:1019703911322
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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 lambda-fuzzy measure. The effectiveness of the approach is demonstrated on two artificial and three real data sets.
引用
收藏
页码:53 / 65
页数:13
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