An Incremental Updating Algorithm of the Computation of a Core Based on the Improved Discernibility Matrix
An Incremental Updating Algorithm of the Computation of a Core Based on the Improved Discernibility Matrix
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发表时间：
2006
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通讯作者：
Yang Ming
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作者：
Yang Ming
粗糙集理论是处理不精确、不完整和不一致数据的一种新的数学工具。属性约简是粗糙集理论研究的重要内容之一。决策表的核心是许多现有属性约简算法的起点。对于核的计算，提出了许多算法。然而，在核心更新方面做的工作很少。因此，本文引入了插入情况下基于可辨矩阵的核计算增量更新算法，在更新可辨矩阵时只插入新的行和列，或者删除一行并更新相应的列，从而显著提高了核的更新效率。理论分析和实验结果表明，本文提出的算法是高效有效的。
Rough set theory is a new mathematical tool to deal with imprecise,incomplete and inconsistent data.Attributes reduction is one of important parts researched in rough set theory.The core of a decision table is the start point to many existing algorithms of attributes reduction.Many algorithms were proposed for the computation of a core.However,very little work has been done in updating of a core.Therefore,this paper introduces an incremental updating algorithm of the computation of a core based on discernibility matrix in the case of inserting,which only inserts a new row and column,or deletes one row and updates corresponding column when updating the decernibility matrix,so the updating efficiency of a core is remarkably improved.Theoretical analysis and experimental results show that the algorithms of this paper are efficient and effective.