Publications:Leverages Based Neural Networks Fusion


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Title Leverages Based Neural Networks Fusion
Author Antanas Verikas and Marija Bacauskiene and Adas Gelzinis
Year 2004
PublicationType Conference Paper
HostPublication Neural information processing
Conference 11th International Conference, ICONIP 2004, Calcutta
Diva url
Abstract To improve estimation results, outputs of multiple neural networks can be aggregated into a committee output. In this paper, we study the usefulness of the leverages based information for creating accurate neural network committees. Based on the approximate leave-one-out error and the suggested, generalization error based, diversity test, accurate and diverse networks are selected and fused into a committee using data dependent aggregation weights. Four data dependent aggregation schemes – based on local variance, covariance, Choquet integral, and the generalized Choquet integral – are investigated. The effectiveness of the approaches is tested on one artificial and three real world data sets.