基于RS理论的快速属性约简求核方法 关键词：属性约简；属性核；差别矩阵 [gap=1200]Key words：attribute reduction；attribute core；discernibility matrix
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Local attribute core 局部属性核
Core Attribute 核心属性 ; 核属性
core attribute set 核属性集
cognitive core attribute 认知核属性
At present, basically all attribute reduction based on Rough Sets is to extract the attribute core through the discernbility matrix, then calculate attribute reduction, but the method is still complex.
目前粗糙集属性约简基本上是通过差别矩阵先求出属性核,然后在属性核的基础上再求出属性约简。
参考来源 - 一种基于rough集的属性约简的改进算法·2,447,543篇论文数据，部分数据来源于NoteExpress
Attempts to point out the role of attribute reduction and analyze an important conception concerned and its importance-attribute core.
文中指出属性约简的作用，及其涉及到的一个重要概念——属性核的概念和重要性。
If your core attribute does not have any value and it's mostly the features you want to sell, you're in for trouble.
如果你的核心属性没有任何价值并且你想卖的主要是外层特征，那你会有麻烦。
These models can be very detailed, showing full entity, relationship and attribute structures and can even have higher-level visualization of the core relationships between coarse grained concepts.
这些模型可能非常详细，显示全部的实体、关系和属性结构，甚至具有粗粒度概念之间的核心关系的更高级的可视化表示。
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