.png){kind=icon}
返回
Analyzing rough set based attribute reductions by extension rule
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2013.07.006.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
An improved discernibility function for rough set based attribute reduction is defined to keep discernibility ability and remove redundant attributes without the precondition of the Positive Region. On the basis of discernibility function, the solution of rough set based attribute reduction can be found by satisfiability methods. With extension rule theory, a satisfiability method, the distribution of solutions with different number of attributes is obtained without enumerating all attribute reductions. Then, it is easy to search the attribute reduction with the smallest number of attributes. In addition, the cost of space and time is analyzed to find factors playing role in the computation of the method. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Attribute reduction
Extension rule
Reduction distribution
Rough set
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
分享收藏Late gadolinium enhancement on cardiac magnetic resonance combined with 123I- metaiodobenzylguanidine scintigraphy strongly predicts long-term clinical outcome in patients with dilated cardiomyopathy.png)
PLOS ONE
OAAI
PLOS ONEIF0
OAAI分享收藏Exploring the boundary region of tolerance rough sets for feature selection面向特征选择的容差粗糙集边界区域研究PATTERN RECOGNITIONOAAI
PATTERN RECOGNITIONIF7.6
OAAI分享收藏分享收藏
查看更多内容