Finding Value Reducts Using Rough Multisets

This paper introduces a new value reduction algorithm for generating rules from consistent and inconsistent examples represented by Multiset Decision Tables (MDT). The algorithm is implemented as stored procedure in MS SQL, hence, it is capable of dealing with very large data sets. The running time of value reduction algorithm is higher than the decision tree program, in general. However, by using a minimum support threshold, the run-time can be improved significantly as indicated in our experiments using the IDS data set of 4 million records.

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