Decision Rule Mining in Rough Set Theory

2011 ◽  
Keyword(s):  
Decision Rule ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Rule Mining

Decision rule mining for machining method chains based on rough set theory

2020 ◽  
Author(s):  
Rui Wang ◽  
Xiangyu Guo ◽  
Shisheng Zhong ◽  
Gaolei Peng ◽  
Lin Wang
Keyword(s):  
Decision Rule ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Rule Mining

Analysis of Time-Series Data by Merging Decision Rules

2017 ◽  
Vol 21 (6) ◽  
pp. 1026-1033
Author(s):  
Yoshiyuki Matsumoto ◽  
Junzo Watada ◽  
◽  
Keyword(s):  
Time Series ◽  
Decision Rule ◽  
Set Theory ◽  
Rough Set ◽  
Time Series Data ◽  
Rough Set Theory ◽  
Decision Rules ◽  
Series Data ◽  
Rule Set ◽  
Analysis Of Time Series

Rough set theory was proposed by Z. Pawlak in 1982. This theory enables the mining of knowledge granules as decision rules from a database, the web, and other sources. This decision rule set can then be used for data analysis. We can apply the decision rule set to reason, estimate, evaluate, or forecast an unknown object. In this paper, rough set theory is used for the analysis of time-series data. We propose a method to acquire rules from time-series data using regression. The trend of the regression line can be used as a condition attribute. We predict the future slope of the time-series data as decision attributes. We also use merging rules to further analyze the time series data.

An Algorithm of Uncertain Reasoning Considering Subjective Factors

2014 ◽  
Vol 989-994 ◽  
pp. 1770-1774
Author(s):  
Ye Hong Han ◽  
Ke Tan Chen ◽  
Heng Shao ◽  
Lin Du
Keyword(s):  
Expert System ◽  
Decision Rule ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Uncertain Reasoning ◽  
System A ◽  
Reasoning Algorithm ◽  
Rules Set ◽  
Better Than

An algorithm of uncertain reasoning which more than one result of a new object can be obtained according to the known knowledge is an important part of an expert system. A new object is an especial decision rule which has only a predecessor. In order to resolve the problem that the differences of attributes’ importance in the new object are not considered in traditional methods of uncertain reasoning, a new uncertain reasoning algorithm based on the rules set which is obtained on the basis of the rough set theory is proposed. In the algorithm, both subjective factors and objective factors in the process of reasoning are considered, and the proportion of subjective factors to objective factors can be controlled by users. So the algorithm is better than the tradition method in flexibility and practicability.

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