Early Detection of Possible Undergraduate Drop Out Using a New Method Based on Probabilistic Rough Set Theory

2019 ◽  
pp. 211-232
Author(s):  
Enislay Ramentol ◽  
Julio Madera ◽  
Abdel Rodríguez
Keyword(s):  
Early Detection ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Drop Out ◽  
New Method

Optimization Analysis on Dynamic Reduction Algorithm

2018 ◽  
Vol 6 (5) ◽  
pp. 447-458
Author(s):  
Yizhou Chen ◽  
Jiayang Wang
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Reduction Process ◽  
New Method ◽  
Reduction Algorithm ◽  
Optimization Analysis ◽  
Sampling Process ◽  
Dynamic Methods ◽  
Definition Of

Abstract On the basis of rough set theory, the strengths of dynamic reduction are elaborated compared with traditional non-dynamic methods. A systematic concept of dynamic reduction from sampling process to the generation of the reduct set is presented. A new method of sampling is created to avoid the defects of being too subjective. And in order to deal with the over-sized time consuming problem in traditional dynamic reduction process, a quick algorithm is proposed within the constraint conditions. We have also proved that dynamic core possesses the essential characteristics of a reduction core on the basis of the formalized definition of the multi-layered dynamic core.

New method for discretization of continuous attributes in rough set theory

2010 ◽  
Vol 21 (2) ◽  
pp. 250-253 ◽  
Author(s):  
Rong Cang ◽  
Xiukun Wang ◽  
Kai Li ◽  
Nanhai Yang
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
New Method

Discretization of Attributes Based on Relative Positive Region of Decision Attribute

2011 ◽  
Vol 271-273 ◽  
pp. 253-257
Author(s):  
Chang Jie Zhou ◽  
Xiao Li ◽  
Dong Wen Zhang ◽  
Ji Qing Qiu
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Real Life ◽  
New Method ◽  
Life Data ◽  
Positive Region ◽  
Real Life Data ◽  
Discrete Methods ◽  
Continuous Attribute

Traditional rough set theory can hardly handle the real-life data which contains continuous attribute. In order to solve this problem, a new method for discretization of continuous attributes based on relative positive region of decision attribute is presented. The method which distinguishes from traditional discrete methods firstly gets the relative positive region of decision attribute, and then discrete continuous attributes with the theorem proved in this paper. Finally, the result of an example shows that our method is efficient and feasible.

Investment Risk Assessment of Hydraulic Engineering Based on Rough Set Theory

2014 ◽  
Vol 584-586 ◽  
pp. 2640-2643
Author(s):  
Zhi Ding Chen ◽  
Hai Man Gao ◽  
Qi Guo
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Rough Set Theory ◽  
Hydraulic Engineering ◽  
New Method ◽  
Decision Table ◽  
Investment Risk

The rough set theory is a new method for analyzing and dealing with data. By using this theory, we proposed a risk assessment algorithm based on rough set theory, which was described in detail in this paper. the decision table can be simplified and redundant attributes can be got rid of A method of inference based on the knowledge of rough sets and an example to show how to acquire the rules of new decision making, thus filling the method with a practical and publicizing value are given.

A new method for measuring uncertainty and fuzziness in rough set theory

2002 ◽  
Vol 31 (4) ◽  
pp. 331-342 ◽  
Author(s):  
Jiye Liang ◽  
K.S. Chin ◽  
Chuangyin Dang ◽  
Richard C.M. Yam
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
New Method

scholarly journals Lower Approximation Reduction Based on Discernibility Information Tree in Inconsistent Ordered Decision Information Systems

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 696 ◽  
Author(s):  
Jia Zhang ◽  
Xiaoyan Zhang ◽  
Weihua Xu
Keyword(s):  
Information System ◽  
Information Systems ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Reduction ◽  
Common Method ◽  
New Method ◽  
Lower Approximation ◽  
Dominance Relations

Attribute reduction is an important topic in the research of rough set theory, and it has been widely used in many aspects. Reduction based on an identifiable matrix is a common method, but a lot of space is occupied by repetitive and redundant identifiable attribute sets. Therefore, a new method for attribute reduction is proposed, which compresses and stores the identifiable attribute set by a discernibility information tree. In this paper, the discernibility information tree based on a lower approximation identifiable matrix is constructed in an inconsistent decision information system under dominance relations. Then, combining the lower approximation function with the discernibility information tree, a complete algorithm of lower approximation reduction based on the discernibility information tree is established. Finally, the rationality and correctness of this method are verified by an example.

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