COX-2 Activity Prediction in Chinese Medicine Using Neural Network Based Ensemble Learning Methods

被引：0
|
作者：
Li, Wei [1 ]
Zhao, Yannan [1 ]
Song, Yixu [1 ]
Yang, Zehong [1 ]
机构：
[1] Tsinghua Univ, Dept Comp Sci, Tsinghua Natl Lab Informat Sci & Technol, State Key Lab Intelligent Technol & Syst, Beijing 100084, Peoples R China
来源：
2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8 | 2008年
关键词：
D O I：
10.1109/IJCNN.2008.4634050
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1853 / 1858
页数：6
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