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A novel rough set approach for classification
- Source :
- GrC
- Publication Year :
- 2006
- Publisher :
- IEEE, 2006.
-
Abstract
- Rough set theory has been widely and successfully used in data mining, especially in classification field. But most existing rough set based classification approaches require computing optimal attribute reduction, which is usually intractable and many problems related to it have been shown to be NP-hard. Although approximate algorithms exist, they also tend to be computationally expensive. This paper presents a novel rough set method for classification, which does not require computing attribute reduction. It stepwise investigates condition attributes and outputs the classification rules induced by them, which is just like the strategy of "on the fly". The theoretical analysis and the empirical study show that the proposed method is effective and efficient. Index Terms—rough set, attribute reduction, data mining, classification
- Subjects :
- business.industry
Computer science
Dominance-based rough set approach
Machine learning
computer.software_genre
Field (computer science)
Electronic mail
Set (abstract data type)
Reduction (complexity)
Information engineering
Artificial intelligence
Rough set
Data mining
Set theory
business
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2006 IEEE International Conference on Granular Computing
- Accession number :
- edsair.doi...........cd28887ec0b6da88eba3b28466431bdd