Attribute reduction of rough sets in mining market value functions | IEEE Conference Publication | IEEE Xplore

Attribute reduction of rough sets in mining market value functions


Abstract:

The linear model of market value functions is a new method for direct marketing. Just like other methods in direct marketing, attribute reduction is very important to dea...Show More

Abstract:

The linear model of market value functions is a new method for direct marketing. Just like other methods in direct marketing, attribute reduction is very important to deal with large databases. We apply the algorithm of attribute reduction, which is based on the combination of rough set theory with the boosting algorithm, to the linear model of market value functions. Experimental results compared with the ELSA/ANN model show that the proposed algorithms can be used effectively in the linear model of market value functions.
Date of Conference: 13-17 October 2003
Date Added to IEEE Xplore: 27 October 2003
Print ISBN:0-7695-1932-6
Conference Location: Halifax, NS, Canada

References

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