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An Attribute Reduction Method Based on Rough Set and SVM and with Application in Oil-Gas Prediction

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2 Author(s)
Ru Nie ; China University of Mining and Technology, China ; Jianhua Yue

With greater generalization performance support vector machine (SVM) is a new machine learning method. Rough set theory is a new powerful tool h dealing with vagueness and uncertainty information. By combining the advantages of two approaches, an original attribute reduction method is proposed in the paper. Moreover, it is applied into oil-gas prediction to solve the problems when support vector machine is directly employed. Experiments and results show the validity and feasibility of the algorithm suggested in the paper.

Published in:

6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007)

Date of Conference:

11-13 July 2007