Two-dimensional performance evaluation model for SMEs based on dominance rough set theory

2014 ◽  
Author(s):  
Ye Chen ◽  
Yong Liao ◽  
Haiyan Xu ◽  
Song Ding
Keyword(s):  
Performance Evaluation ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Evaluation Model ◽  
Two Dimensional ◽  
Performance Evaluation Model

ROUGH CLUSTERING FOR CANCER DATASETS

2012 ◽  
Vol 09 ◽  
pp. 240-258 ◽  
Author(s):  
TUTUT HERAWAN
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Accurate Diagnosis ◽  
Divide And Conquer ◽  
Machine Learning Techniques ◽  
Two Dimensional ◽  
Learning Techniques ◽  
Diagnostic Capability ◽  
User Friendly

Cancer is becoming a leading cause of death among people in the whole world. It is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. Expert systems and machine learning techniques are gaining popularity in this field because of the effective classification and high diagnostic capability. This paper presents the application of rough set theory for clustering two cancer datasets. These datasets are taken from UCI ML repository. The method is based on MDA technique proposed by [11]. To select a clustering attribute, the maximal degree of the rough attributes dependencies in categorical-valued information systems is used. Further, we use a divide-and-conquer method to partition/cluster the objects. The results show that MDA technique can be used to cluster to the data. Further, we present clusters visualization using two dimensional plot. The plot results provide user friendly navigation to understand the cluster obtained.

Research on Information Technology with Character Pattern Recognition Method Based on Rough Set Theory

2014 ◽  
Vol 886 ◽  
pp. 519-523 ◽  
Author(s):  
Yong Li Liu
Keyword(s):  
Information Technology ◽  
Pattern Recognition ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Decision Rules ◽  
Pattern Recognition Method ◽  
Two Dimensional ◽  
Recognition Method ◽  
Two Dimensional Image

Character Pattern recognition is widely used in the information technology field. This paper proposes a method of character pattern recognition based on rough set theory. By giving the characters two dimensional image, defining the location of the characteristic and abstracting the characteristic value, the knowledge table and table reduction can be ascertained. Then the decision rules can be deduced. Through the simulation of 26 English alphabets, the results illustrate this methods validity and correctness.

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