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International Conference on Information Technology and Computer Science, 3rd (ITCS 2011)

V. E. Muhin
V. E. Muhin
National Technical University of Ukraine
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W. B. Hu
W. B. Hu
Wuhan University
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ASME Press
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In this paper, we present a neural network ensemble method called DS-NNE which is based on dataset splitting. In order to get better classification results, the DS-NNE method performs the following tasks: (1) performs gene selection using t-test and f-test to remove the redundant genes. (2) divides the original training dataset into k disjoint subsets; (3) performs random re-sampling k-1 out of k subsets to get a training dataset and trains a neural network classifier on the generated dataset, then repeats the training procedure n times to obtain n neural networks. (4) predicts the class label from the unknown data...

1. Introduction
2. Method
3. Experiments and Results
4. Conclusions
5. Acknowledgments
6. References
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