Redundancy reduction: does it help associative classifiers?

SAC, pp. 867-874, 2016.

Cited by: 4|Bibtex|Views18|DOI:https://doi.org/10.1145/2851613.2851649
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

Abstract:

The number of classification rules discovered in associative classification is typically quite large. In addition, these rules contain redundant information since classification rules are obtained from mined frequent itemsets and the latter are known to be repetitive. In this paper we investigate through an empirical study the performance...More

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