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COX-2 activity prediction in Chinese medicine using neural network based ensemble learning methods

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4 Author(s)
Wei Li ; Dept. of Comput. Sci., Tsinghua Univ., Beijing ; Yannan Zhao ; Yixu Song ; Zehong Yang

In this paper, neural network based ensemble learning methods are introduced in predicting activities of COX-2 inhibitors in Chinese medicine quantitative structure-activity relationship (QSAR) research. Three different ensemble learning methods: bagging, boosting and random subspace are tested using neural networks as basic regression rules. Experiments show that all three methods, especially boosting, are fast and effective ways in the activity prediction of Chinese medicine QSAR research, which is generally based on a small amount of training samples.

Published in:

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Date of Conference:

1-8 June 2008

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