计算机科学 ›› 2016, Vol. 43 ›› Issue (1): 40-43.doi: 10.11896/j.issn.1002-137X.2016.01.009
• CRSSC-CWI-CGrC2015 • 上一篇 下一篇
杨习贝,颜旭,徐苏平,于化龙
YANG Xi-bei, YAN Xu, XU Su-ping and YU Hua-long
摘要: 属性约简是粗糙集理论的核心研究内容之一。借鉴于贪心策略的启发式算法是求解约简的一种有效技术手段。传统的启发式算法使用了决策系统中的所有样本,但实际上每个样本对约简的贡献程度是不同的,这在一定程度上增加了启发式算法的时间消耗。为解决这一问题,提出了一种基于样本选择的启发式算法,该算法主要分为3步:首先从样本集中挑选出重要的样本;然后利用选取出的样本构建新的决策系统;最后利用启发式算法求解约简。实验结果表明,新算法能够有效地减少约简的求解时间。
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