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一种基于粗糙集理论的连续属性离散化新算法*
引用本文:李慧,闫德勤,韩丽. 一种基于粗糙集理论的连续属性离散化新算法*[J]. 计算机应用研究, 2010, 27(1): 77-78. DOI: 10.3969/j.issn.1001-3695.2010.01.022
作者姓名:李慧  闫德勤  韩丽
作者单位:1. 辽宁师范大学,计算机系,辽宁,大连,116081
2. 柴河林业局第一小学,黑龙江,海林,157131
基金项目:国家自然科学基金资助项目(60372071);中国科学院自动化研究所复杂系统与智能科学重点实验室开放课题基金资助项目(20070101);辽宁省教育厅高等学校科学研究基金资助项目(2008344);大连市科技局科技计划资助项目(2007A10GX117)
摘    要:粗糙集理论中要求离散化保持原有决策系统的不可分辨关系,但以往的一些算法在离散过程中会使近似精度控制在可以接受的范围,即允许一定的错分。针对此不足,在保证决策属性绝对不改变的情况下,提出一种新的区间拆分方法,更合理有效地对连续属性进行离散化。实验通过C4.5和支持向量机分别对离散化后的数据进行识别与分类预测,实验结果证明了算法的有效性。

关 键 词:连续属性离散化; 粗糙集; 决策表; 离散区间; 数据挖掘

Novel algorithm for discretization of continuous attributes based on rough sets theory
LI Hui,YAN De-qin,HAN Li. Novel algorithm for discretization of continuous attributes based on rough sets theory[J]. Application Research of Computers, 2010, 27(1): 77-78. DOI: 10.3969/j.issn.1001-3695.2010.01.022
Authors:LI Hui  YAN De-qin  HAN Li
Affiliation:(1.Dept. of Computer Science, Liaoning Normal University, Dalian Liaoning 116081, China; 2.The Primary School of Chaihe, Hailin Heilongjiang 157131, China )
Abstract:The rough set required that discretization should be maintained indiscernibility of the original decision-making system, however, many algorithms before permitted approximate quality descended controlled certain scope. This paper proposed a novel method of splitting interval. The novel algorithm was more reasonable and effective to discretization of continual attribute, and assured not to change decision-making attributes. By using C4.5 and SVM, performed the experiments respectively with the results of discreted data. The experiment results show that the presented algorithm is effective.
Keywords:discretization of continuous attributes   rough set   decision table   discretization interval   data mining
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