Incremental Algorithm of Pawlak Reduction Based on Attribute Order
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摘要: 为了对动态变化的决策表进行属性约简处理,在给定的属性序下,提出了一种基于分辨矩阵元素集的 增量式Pawlak约简算法.该算法根据新增对象的不同情况快速更新分辨矩阵元素集,并依据其元素的变化,在 给定属性序下快速更新Pawlak约简.实例和仿真实验结果表明,该算法是有效、可行的,与非增量式算法相比, 效率平均提高91.4%.Abstract: In order to update the attribute reduction of dynamic decision tables, an incremental algorithm of Pawlak reduction with a given attribute order was proposed based on a discernibility matrix element set. To different newly added objects this algorithm updates the discernibility matrix element set quickly. Thus, from the change of its elements the original Pawlak reduction can be updated effectively based on the given attribute order. An illustrative example and simulation experiment show that compared with the non-incremental algorithm, the proposed algorithm is efficient and feasible and has a 91.4% improvement in average efficiency.
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Key words:
- rough set /
- attribute reduction /
- increment /
- attribute order /
- discernibility matrix
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