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变精度粗糙集模型中β参数范围的确定 被引量:6

Confirming the Range of β Parameter in the Variable Precision Rough Sets Model
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摘要 正确分类率β是变精度粗糙集模型中重要的参数之一.针对变精度粗糙集中β参数的确定缺乏可预见性的问题,提出了在确定近似分类质量γ下β取值范围的确定方法.首先在选取特定β值的情况下,根据约简条件求取所有β约简;然后在近似分类质量保持不变的前提下,确定β参数的取值范围;最后通过一个算例验证了该方法的有效性. The correct classification rate β is one of the important parameter of variable precision rough sets model. To the problem that the variable precision rough set lacks a feasible method to determine the β parameter; in this paper, an effective method is developed to confirm the range of β value by the γ value of approximate quality of classification. First, we calculate all the value of β reduction according to reduction condition on the base that β value is certain.Furthermore, we will confirm the range of β value on the base that the approximate quality of classification is fixed; Finally, an example is given to approve the effectiveness of the nronosed method.
作者 刘妍琼 钟波
出处 《湖南理工学院学报(自然科学版)》 CAS 2008年第1期11-13,共3页 Journal of Hunan Institute of Science and Technology(Natural Sciences)
关键词 变精度粗糙集 近似分类质量 β约简 β参数 variable precision rough sets approximate quality of classification β reduction β parameter
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  • 1Pawlak Z. Rough sets[J]. International Journal of Computer and Information Sciences, 1982,11:341 -356.
  • 2Slowinski R, Vanderpooten D. A generalized definition of rough approximations based on similarity [ J ]. IEEE Transaction on Knowledge and Data Engineering, 2000, 12(2) : 331 - 336.
  • 3Kryszkiewicz M. Rough set approach to incomplete information systems [J]. Information Sciences, 1995, 112: 39- 49.
  • 4Ziarko W. Variable precision rough set model [J]. Journal of Computer and System Sciences, 1993,46(1) :39 - 59.
  • 5Beynon M. Reducts within the variable precision rough sets model: A further investigation [ J]. European Journal of Operational Research, 2001, 124:592 - 605.
  • 6Aijun An, Ning Shan,et al. Discovering rules for water demand prediction: An enhanced rough-set approach [J]. Applications of Artificial Intelligence, 1996,9(6) : 645 - 653.
  • 7王珏,王任,苗夺谦,郭萌,阮永韶,袁小红,赵凯.基于Rough Set理论的“数据浓缩”[J].计算机学报,1998,21(5):393-400. 被引量:239
  • 8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. 被引量:512
  • 9王国胤.Rough集理论在不完备信息系统中的扩充[J].计算机研究与发展,2002,39(10):1238-1243. 被引量:306
  • 10张文修,米据生,吴伟志.不协调目标信息系统的知识约简[J].计算机学报,2003,26(1):12-18. 被引量:191

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