Combining the max rate sampling strategy and the discernibility matrix together creates the dynamic reduct algorithm.
结合概率抽样策略和差别矩阵构造出一个动态约简算法。
参考来源 - 基于粗糙集理论的动态约简研究Lastly, rules extraction method based tole-rance relation and discernibility matrix.
在决策规则的获取中,分析了基于相容关系和区分矩阵的规则获取算法。
参考来源 - 粗糙集理论在不完备信息系统知识获取中的应用研究An extracting rules algorithm based on class feature matrix is presented,which has made use of the characteristic of discernibility matrix.
充分考虑了可辨识矩阵的特性,提出一种基于类别特征矩阵的决策规则提取算法。
参考来源 - 基于类别特征矩阵的决策规则提取算法Firstly a reduct is derived for each class of data, and then for each class a discernibility matrix and a merger matrix are constructed and rules for this class are extracted based on the two matrices.
首先获得每类数据的属性约简；然后为每类数据构造一个分辨矩阵和一个合并矩阵,通过两个矩阵的交互作用逐类抽取规则。
参考来源 - 分类数据挖掘中若干基本问题的研究In the reference 54, several kinds of attribute reduction have been put forward; we know provide two kinds of new discernibility matrix of flower and upper distribution reduction, which are equivalence to discernibility matrix in the reference54.
针对文献54中提出的几种属性约简,给出了β上、下分布约简的两种新的可辨识矩阵,与文献54中的可辨识矩阵是等价的。
参考来源 - 变精度广义粗糙集模型·2,447,543篇论文数据，部分数据来源于NoteExpress
Secondly, we investigate the method of discernibility matrix and function.
其次，我们对差别矩阵差别函数的方法进行了研究。
In this paper, application about discernibility matrix arithmetic and HORAFA arithmetic based on the rough set theory is introduced.
简要介绍了粗糙集理论中区分矩阵算法和HORAFA算法在知识约简中的应用。
An extracting rules algorithm based on class feature matrix is presented, which has made use of the characteristic of discernibility matrix.
充分考虑了可辨识矩阵的特性，提出一种基于类别特征矩阵的决策规则提取算法。
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