1. X. Chai, L. Deng, Q. Yang, C.X. Ling, Test-cost sensitive naive bayes classification, in: Fourth IEEE International Conference on Data Mining, ICDM’04, 2004, pp. 51–58.
2. Smote: synthetic minority over-sampling technique;Chawla;J. Artif. Intell. Res.,2002
3. C. Chen, A. Liaw, L. Breiman, Using random forest to learn imbalanced data, University of California Berkeley, 2004.
4. D.M. Chickering, Learning bayesian networks is np-complete, in: Learning from Data, 1996, pp. 121–130.
5. Approximating discrete probability distributions with dependence trees;Chow;IEEE Trans. Inf. Theory,1968