Wu Xiaodong, Vipin K, Quinlan J R, et al. Top 10 Algorithms in Data Mining. Knowledge Information System, 2008, 14(1): 1-37
[2]
Dougherty J, Kohavi R, Sahami M. Supervised and Unsupervised Discretization of Continuous Feature // Proc of the 12th International Conference on Machine Learning. Edinburgh, UK, 1995: 194-202
[3]
Liu Huan, Setiono R. Feature Selection via Discretization. IEEE Trans on Knowledge and Data Engineering, 1997, 9(4): 642-645
[4]
Su C T, Hsu J H. An Extended Chi2 Algorithm for Discretization of Real Value Attributes. IEEE Trans on Knowledge and Data Engineering, 2005, 17(3): 437-441
[5]
Sang Yu, Yan Deqin, Liang Hongxia, et al. Modification to Algorithms of the Series of Chi2 Algorithm. Journal of Chinese Computer Systems, 2009, 30(3): 524-529 (in Chinese)(桑 雨,闫德勤,梁宏霞,等.对Chi2系列算法的改进方法.小型微型计算机系统, 2009, 30(3): 524-529)
[6]
Fayyad U, Irani K. Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning // Proc of the 13th International Joint Conference on Artificial Intelligence. Chambery, France, 1993: 1022-1027
[7]
Xie Hong, Cheng Haozhong, Niu Dongxiao. Discretization of Continuous Attributes in Rough Set Theory Based on Information Entropy. Chinese Journal of Computers, 2005, 28(9): 1570-1574 (in Chinese)(谢 宏,程浩忠,牛东晓.基于信息熵的粗糙集连续属性离散化算法.计算机学报, 2005, 28(9): 1570-1574)
[8]
Kurgan L A, Cios K J. CAIM Discretization Algorithm. IEEE Trans on Knowledge and Data Engineering, 2004, 16(2): 145-153
[9]
Tai C J, Lee C I, Yang W P. A Discretization Algorithm Based on Class-Attribute Contingency Coefficient. Information Sciences, 2008, 178(3): 714-731.
[10]
Li Gang.An Unsupervised Discretization Algorithm Based on Mixture Probabilistic Model. Chinese Journal of Computers, 2002, 25(2): 158-164 (in Chinese)(李 刚.基于混合概率模型的无监督离散化算法.计算机学报, 2002, 25(2): 158-164)
[11]
Ruiz F J, Angulo C, Agell N. IDD: A Supervised Interval Distance-Based Method for Discretization. IEEE Trans on Knowledge and Data Engineering, 2008, 20(9): 1230-1238
[12]
Jin Ruoming, Breitbart Y, Muoh C. Data Discretization Unification. Knowledge and Information System, 2008, 14(1): 115-142
[13]
Hansen M H, Yu Bin. Model Selection and the Principle of Minimum Description Length. Journal of the American Statistical Association, 2001, 96(454): 746-774
[14]
Fazlollah M R. An Introduction to Information Theory. New York, USA: Dover Publications, 1994
[15]
Mussard S, Seyte F, Terraza M. Decomposition of Gini and the Generalized Entropy Inequality Measures. Economic Bulletin, 2003, 4(7): 1-6
[16]
Pawlak Z. Rough Sets. International Journal of Computer and Information Sciences, 1982, 11(5): 341-356
[17]
Li Linshu. Probability and Mathematical Statistics. Beijing, China: China Renmin University Press, 2006 (in Chinese)(李林曙. 概率论与数理统计. 北京: 中国人民大学出版社, 2006)
[18]
Hsu C N, Huang H J, Wong T T. Why Discretization Works for Nave Bayesian Classifiers // Proc of the 17th International Conference on Machine Learning. Stanford, USA, 2000: 309-406
