【摘 要】
：
属性约简一直是粗糙集理论研究的热点问题.近年来,基于启发式的属性约简方法研究逐步兴起,其核心内容是在约简过程中增添最重要的属性,但此类算法存在复杂度高和时间消耗大等问题.针对此,提出一种基于序贯三支决策的属性约简方法.将属性作为划分策略的治略对象,依据属性重要度进行三支治略:根据属性重要度和阈值将属性分为正划分集合、负划分集合和延迟划分集合.发生正划分的属性集合被接受添加到决策属性集,负划分的属性集合被拒绝添加到决策属性集,对延迟决策的属性集合重复以上操作直至约简结果满足约束条件.此算法根据划分结果选取加
【机 构】
：
哈尔滨师范大学计算机科学与信息工程学院,黑龙江哈尔滨150025
论文部分内容阅读
属性约简一直是粗糙集理论研究的热点问题.近年来,基于启发式的属性约简方法研究逐步兴起,其核心内容是在约简过程中增添最重要的属性,但此类算法存在复杂度高和时间消耗大等问题.针对此,提出一种基于序贯三支决策的属性约简方法.将属性作为划分策略的治略对象,依据属性重要度进行三支治略:根据属性重要度和阈值将属性分为正划分集合、负划分集合和延迟划分集合.发生正划分的属性集合被接受添加到决策属性集,负划分的属性集合被拒绝添加到决策属性集,对延迟决策的属性集合重复以上操作直至约简结果满足约束条件.此算法根据划分结果选取加入决策属性集的元素集合,从而大大降低了时间消耗.实验选取了8组UCI数据集,在传统全局约简条件和集成约简条件下分别进行,实验结果表明,本文提出算法在两种条件下能够在保证分类精度的前提下,有效降低时间消耗.
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