Discovering attributes dependency for categorical data set based on soft set theory for better decision making
Attribute dependency concludes the association between attributes for better accurate decision making. However, the task involved in identifying the relation between categorical values in data set is a complex process. This main focus of this paper is to determine the attribute dependency in a real...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hikari Ltd.
2015
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/7137/1/FH02-FIK-16-06428.jpg http://eprints.unisza.edu.my/7137/ |
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| Summary: | Attribute dependency concludes the association between attributes for better accurate decision making. However, the task involved in identifying the relation between categorical values in data set is a complex process. This main focus of this paper is to determine the attribute dependency in a real world application. The proposed method is based on the notion of mapping inclusion from the soft set theory. The categorical data is transformed to predicate and value set to discover the dependency among the attributes. The result shows that the attribute dependencies obtained are comparable to the rough set approach. |
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