Discretization - Data Preprocessing in Data Mining - page 272

an improved version of Chi2 in terms of accuracy, removing the user parame-
ter choice. We check and measure the actual improvement. In [ 122 ], the authors
develop an intense theoretical and analytical study concerning Naïve Bayes and
propose PKID and FFD according to their conclusions. Thus, we corroborate that
PKID is the best suitable method for Naïve Bayes and even for KNN . Finally, we
may note that CAIM is one of the simplest discretizers and its effectiveness has
also been shown in this study.
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