Improving classification through ensemble neural networks

Khobaib Zaamout, John Z. Zhang
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引用次数: 6

Abstract

We consider using neural networks as an ensemble technique to improve classification accuracy. Neural networks are among the best techniques used for classification. In this work, we make use of ensemble approach to combine individual neural networks' outputs by another neural network. Furthermore, we propose to include original data as additional inputs for the ensemble neural network. The effectiveness of our proposed approach is demonstrated through a series of experiments on real and synthetic datasets.
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通过集成神经网络改进分类
我们考虑使用神经网络作为集成技术来提高分类精度。神经网络是用于分类的最佳技术之一。在这项工作中,我们使用集成方法将单个神经网络的输出与另一个神经网络相结合。此外,我们建议将原始数据作为集成神经网络的附加输入。通过在真实数据集和合成数据集上的一系列实验证明了我们提出的方法的有效性。
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