The attribute reduction and rules are gained.
对矩阵进行化简得到属性约简并生成规则。
Conduct attribute reduction and value reduction.
将决策表进行属性约简，值约简。
Attribute reduction is the core of rough sets theory.
属性约简是粗糙集理论的核心内容。
Attribute reduction is a research focus in rough set theory.
属性约简是粗糙集理论中的一个研究重点。
But it is a NP-Hard problem to get the minimal attribute reduction.
但求取任意问题的最小属性集是一个NP难问题。
The attribute reduction is one of the cores of Rough Set (RS) theory.
属性约简是粗糙集(RS)理论的核心内容之一。
Attribute reduction is an important concept in rough sets data analysis.
属性约简是粗糙集用于数据分析的重要概念。
Attribute reduction is a core subject in the domain of rough set theory.
属性约简问题是粗糙集理论中一个核心的研究课题。
Attribute reduction is one of the key problems for the knowledge acquisition.
属性约简是知识获取中的关键问题之一。
It is the need of data processing in attribute reduction about large datasets.
属性约简是对大数据集进行数据处理的需要。
Attribute reduction is one of the most important parts in knowledge acquisition.
属性约简是知识获取中最重要的部分之一。
Then, an attribute reduction algorithm based on indiscernibility matrix is introduced.
给出了基于不可区分矩阵的属性频率约简算法。
Proposed an algorithm of attribute reduction based on attribute importance of rough set.
提出一种基于粗糙集属性重要性的属性约简算法。
And then a relative attribute reduction algorithm is mentioned based on information entropy.
后面又提到了基于信息熵的相对属性约简算法。
The process of attribute reduction is analyzed in assembly knowledge discovery based on rough set.
分析了基于粗糙集理论的装配知识发现中属性归约的过程。
Then the author's researches on data discretization and attribute reduction are introduced in detail.
随后论文重点对作者在数据离散和属性约简两个方面做的研究工作进行了阐述。
This paper discusses algebra properties and changing law of entropy for some attribute reduction definitions.
讨论几种属性约简定义的代数性质和信息熵改变规律。
Comparing with the old attribute reduction algorithms, it has lower complex degree and has powerful usability.
与现有的决策表属性约简算法进行比较，它具有较低的复杂度和较强的可使用性。
These results provide theoretical basis and applied foundation for attribute reduction in inconsistent information system.
这为不一致信息系统的属性约简提供了理论依据与算法。
In this paper we present a novel hybrid algorithm based on attribute reduction of RS and classification principles of SVM.
结合粗糙集的属性约简和支持向量机的分类机理，提出了一种混合算法。
And on this basis, an attribute reduction algorithm based on the improved differential evolutionary algorithm was put forward.
并在此基础上提出了基于差分演化算法的属性约简算法。
For the sake of different applications, various definitions of attribute reduction have been proposed by different researchers.
出于应用目的，许多学者提出了各种不同的属性约简概念。
The time complexity and space complexity of the traditional attribute reduction algorithm using discernible matrix are quite big.
传统的利用区分矩阵进行属性约简算法，其时间复杂度和空间复杂度很大。
To improve the efficiency of attribute reduction, a rapid reduction algorithm based on conditional information quantity is proposed.
为提高粗集约简的效率，提出了一种基于条件信息量的快速粗集约简算法。
Finally, the equivalence properties between Boolean matrix representation and algebra representation of attribute reduction are proved.
最后证明了属性约简在布尔矩阵和代数两种不同表示下是等价的。
The attribute reduction quality, which includes reduction ratio and approximate quality, is defined to scale the reduction effectiveness.
提出约简质量的定义，从属性约简率和近似质量两方面来衡量约简效果。
But the attribute reduction is a NP problem, the attribution reduction and decision rule reduction will be solved by method of elicitation.
但是属性约简是一个NP问题，对属性的约简和决策规则的约简只能通过启发式算法实现。
Under the condition of unchanged classification and decision abilities, attribute reduction is to delete irrelative or unimportant attribute.
属性约简要求在保持知识库的分类和决策能力不变的条件下，删除不相关或不重要的属性。
Through examples, it shows that attribute reduction of an inconsistent decision table cannot entirely be represented by information quantity.
并举例说明，对于不一致决策表，其属性的约简不能用信息量来等价表示。
In data mining with Attribute-Oriented generalization (AOG), attribute reduction and concept generalization can not part from concept hierarchy.
在面向属性归纳(AOG)的数据挖掘中，属性归约及概念归纳都离不开概念层次。
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