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International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)

By
Chen Ming
Chen Ming
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ISBN:
9780791859902
No. of Pages:
1400
Publisher:
ASME Press
Publication date:
2011

Decision-making process usually requires enough information to support, but information collection process is affected by various uncertain factors, and therefore, some incomplete data is very necessary to be processed before they are using for the decision-making. Based on the rough set theory, some data processing methods for the incomplete information system are analyzed in detail. Mainly, a data complement method based on ROUSTIDA algorithm is built to process the incomplete data, as an example, the UCI database of Iris data set is put into application, and the application results show that the method has good rationality.

Abstract
Keywords:
Introduction
1 Relationships Based on Tolerance Rough Set Model Expansion
2 Decision Table Discretization
3 Boolean Logic and Rough Set Theory Combined with the Discrete Algorithm
4 Rough Set Theory Based on Incomplete Data Analysis Methods
5 Application Analysis
6 Conclusion
Acknowledgments
References
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