References
- Lai J H. Ensemble Learning for Text Classification[J]. 2017.
- Wang G, Sun J, Ma J, et al. Sentiment classification: The contribution of ensemble learning[J]. Decision support systems, 2014, 57: 77–93.
- Xia R, Zong C, Li S. Ensemble of feature sets and classification algorithms for sentiment classification[J]. Information Sciences, 2011, 181(6): 1138–1152.
- Jia J, Liu Z, Xiao X, et al. pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach[J]. Journal of theoretical biology, 2016, 394: 223–230.
- Rodriguez J J, Kuncheva L I, Alonso C J. Rotation forest: A new classifier ensemble method[J]. IEEE transactions on pattern analysis and machine intelligence, 2006, 28(10): 1619–1630.
- Wu Z, Lin W, Zhang Z, et al. An Ensemble Random Forest Algorithm for Insurance Big Data Analysis[C]// Computational Science and Engineering (CSE) and Embedded and Ubiquitous Computing (EUC), 2017 IEEE International Conference on. IEEE, 2017, 1: 531–536.
- Li N, Jiang Y, Zhou Z H. Multi-label Selective Ensemble[C]// International Workshop on Multiple Classifier Systems. Springer, Cham, 2015: 76–88.
- Qian C, Yu Y, Zhou Z H. Pareto Ensemble Pruning[C]// AAAI. 2015: 2935–2941.