A Multivariate Discretization Algorithm Based on Multiobjective Optimization
Rafael Zamudio-Reyes, Nicandro Cruz-Ramírez, Efrén Mezura‐Montes · 2017
In this paper, a new multivariate discretization algorithm called multiCAIM is presented. Discretization consists of transforming continuous attributes into discrete ones. Most discretization algorithms are univariate and find a discretization scheme using only a discretization criterion. On the other hand, the proposed approach obtains a set of discretization schemes guiding the search by using a discretization criterion and the prediction accuracy of Naïve Bayes. The obtained datasets using multiCAIM are evaluated employing three popular and competitive classifiers: Naïve Bayes, KNN and C4.5. The overall assessment suggests that the proposed algorithm outperforms classical discretizers, moreover, it allows to the expert to select more than one discretization scheme.