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基于近似决策熵的属性约简

DOI: 10.13195/j.kzyjc.2013.1527, PP. 65-70

Keywords: 粗糙集,属性约简,信息熵,近似决策熵

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Abstract:

粗糙集理论已被证明是一种有效的属性约简方法.目前有许多启发式属性约简算法已被提出,其中基于信息熵的属性约简算法受到了广泛的关注.为此,针对现有的基于信息熵的属性约简算法问题,定义一种新的信息熵模型—–近似决策熵,并提出一种基于近似决策熵的属性约简(ADEAR)算法.通过在多个UCI数据集上的实验表明,与现有算法相比,ADEAR算法能够获得较小的约简和较高的分类精度,具有相对较低的计算开销.

References

[1]  Hu Q H, Xie Z X, Yu D R. Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation[J]. Pattern Recognition, 2007, 40(12): 3509-3521.
[2]  Hu Q H, Yu D R, Liu J F, et al. Neighborhood
[3]  rough set based heterogeneous feature subset selection[J]. Information Sciences, 2008, 178(18): 3577-3594.
[4]  Miao D Q, Zhao Y, Yao Y Y, et al. Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model[J]. Information Sciences, 2009, 179(24): 4140-4150.
[5]  Qian Y H, Liang J Y, Pedrycz W, et al. Positive approximation: An accelerator for attribute reduction in rough set theory[J]. Artificial Intelligence, 2010, 174(9/10): 597-618.
[6]  杨明, 杨萍. 基于广义差别矩阵的核和属性约简算法[J]. 控制与决策, 2008, 23(9): 1049-1054.
[7]  (Yang M, Yang P. Algorithms based on general discernibility matrix for computation of a core and attribute reduction[J]. Control and Decision, 2008, 23(9): 1049-1054.)
[8]  李鸿. 基于条件信息量的知识相对约简算法[J]. 中国矿业大学学报, 2005, 34(3): 378-382.
[9]  (Li H. Algorithm for relative reduction of knowledge in information systems based on a conditional information quantity[J]. J of China University of Mining and Technology, 2005, 34(3): 378-382.)
[10]  Shannon C E. The mathematical theory of communication[J]. Bell System Technical J, 1948, 27(3/4): 373-423.
[11]  D¨untsch I, Gediga G. Uncertainty measures of rough set prediction[J]. Artificial Intelligence, 1998, 106(1): 109-137.
[12]  Liang J Y, Shi Z Z, Li D Y, et al. Information entropy, rough entropy and knowledge granularity in incomplete information systems[J]. Int J of General Systems, 2006, 35(6): 641-654.
[13]  代建华, 潘云鹤. 一种基于分类一致性的决策规则获取算法[J]. 控制与决策, 2004, 19(10): 1086-1090.
[14]  (Dai J H, Pan Y H. Algorithm for acquisition of decision rules based on classification consistency rate[J]. Control and Decision, 2004, 19(10): 1086-1090.)
[15]  Zhao H B, Jiang F, Wang C P. An approximation decision entropy based decision tree algorithm and its application in intrusion detection[C]. Proc of the 6th Int Conf on Rough Set and Knowledge Technology. Chengdu: Springer-Verlag, 2012: 101-106.
[16]  徐章艳, 刘作鹏, 杨炳儒, 等. 一个复杂度为max(O(∣C∣∣U∣),O(∣C∣2∣U/C∣)) 的快速属性约简算法[J]. 计算机学报, 2006, 29(3): 391-399.
[17]  (Xu Z Y, Liu Z P, Yang B R, et al. A quick attribute reduction algorithm with complexity of max(O(∣C∣∣U∣),O(∣C∣2∣U/C∣))[J]. Chinese J of Computers, 2006, 29(3): 391-399.)
[18]  Bay S D. The UCI KDD repository[DB/OL]. University of
[19]  California, Irvine, 1999. http://kdd.ics.uci.edu.?
[20]  Wroblewski J. Finding minimal reducts using genetic algorithms[C]. The 2nd Annual Joint Conf on Information Sciences. North Carolina: Atlantis Press, 1995: 186-189.
[21]  Wang X Y, Yang J, Teng X L, et al. Feature selection based on rough sets and particle swarm optimization[J]. Pattern Recognition Letters, 2007, 28(4): 459-471.
[22]  Skowron A, Bazan J, Son N H, et al. RSES 2.2 User’s Guide[EB/OL]. [2005-01-19]. http://logic.mimuw.edu.pl/rses.
[23]  Hu X H. Knowledge discovery in databases: An attribute-oriented rough set approach[D]. Regina: Regina University, 1995.
[24]  Pawlak Z. Rough sets[J]. Int J of Computer and Information Sciences, 1982, 11(5): 341-356.
[25]  苗夺谦, 胡桂荣. 知识约简的一种启发式算法[J]. 计算机研究与发展, 1999, 36(6): 681-684.
[26]  (Miao D Q, Hu G R. An heuristic algorithm of knowledge reduction[J]. Computer Research and Development, 1999, 36(6): 681-684.)
[27]  王国胤, 于洪, 杨大春. 基于条件信息熵的决策表约简[J]. 计算机学报, 2002, 25(7): 759-766.
[28]  (Wang G Y, Yu H, Yang D C. Decision table reduction based on conditional information entropy[J]. Chinese J of Computers, 2002, 25(7): 759-766.)
[29]  Liang J Y, Xu Z B. The algorithm on knowledge reduction in incomplete information systems[J]. Int J of Uncertainty, Fuzziness and Knowledge-Based Systems, 2002, 10(1): 95-103.
[30]  Hu K Y, Lu Y C, Shi C Y. Feature ranking in rough sets[J]. AI Communication, 2003, 16(1): 41-50.

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