Abstract
In this paper, we address the problem of generating relevant classification rules. Within this framework we are interested in rules of the form a 1 ∧ a 2… ∧ a n ⇒b which allow us to propose a new approach based on the cover set and genetic algorithms principle. This approach allows obtaining frequent and rare rules while avoiding making a breadth search. It is an improvement of afortiori approach. Moreover, our proposed algorithm can extract the classifier using a clustering for the attributes which allows to minimize the processing of the classifier building.
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Bouzouita, I. (2014). An Optimized Classification Approach Based on Genetic Algorithms Principle. In: Herawan, T., Ghazali, R., Deris, M. (eds) Recent Advances on Soft Computing and Data Mining. Advances in Intelligent Systems and Computing, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-319-07692-8_41
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DOI: https://doi.org/10.1007/978-3-319-07692-8_41
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07691-1
Online ISBN: 978-3-319-07692-8
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