Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10321737 | Expert Systems with Applications | 2015 | 13 Pages |
Abstract
We tested our approach on seventeen real-world datasets and compared the achieved results with the ones obtained by using both a non-fuzzy associative classifier, namely CMAR, and two recent state-of-the-art classifiers, namely FARC-HD and D-MOFARC, based on fuzzy association rules. Using non-parametric statistical tests, we show that our approach outperforms CMAR and achieves accuracies similar to FARC-HD and D-MOFARC.
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Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Michela Antonelli, Pietro Ducange, Francesco Marcelloni, Armando Segatori,