首页> 外文会议>International Conference on Intelligent Computing(ICIC 2006); 20060816-19; Kunming(CN) >The Mixture of Neural Networks Adapted to Multilayer Feedforward Architecture
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The Mixture of Neural Networks Adapted to Multilayer Feedforward Architecture

机译:适应多层前馈架构的神经网络混合

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The Mixture of Neural Networks (MixNN) is a Multi-Net System based on the Modular Approach. The MixNN employs a neural network to weight the outputs of the expert networks. This method decompose the original problem into subproblems, and the final decision is taken with the information provided by the expert networks and the gating network. The neural networks used in MixNN are quite simple so we present a mixture of networks based on the Multilayer Feedforward architecure, called Mixture of Multilayer Feedforward (MixMF). Finally, we have performed a comparison among Simple Ensemble, MixNN and MixMF. The methods have been tested with six databases from the UCI repository and the results show that MixMF is the best performing method.
机译:神经网络的混合(MixNN)是基于模块化方法的多网络系统。 MixNN使用神经网络对专家网络的输出进行加权。该方法将原始问题分解为子问题,并根据专家网络和选通网络提供的信息做出最终决定。 MixNN中使用的神经网络非常简单,因此我们介绍了一种基于多层前馈架构的混合网络,称为多层前馈混合物(MixMF)。最后,我们在Simple Ensemble,MixNN和MixMF之间进行了比较。该方法已使用UCI储存库中的六个数据库进行了测试,结果表明MixMF是性能最好的方法。

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