An Extended Comparison of Six Approaches to Discretization - A Rough Set Approach.

We present results of extensive experiments performed on nine data sets with numerical attributes using six promising discretization methods. For every method and every data set 30 experiments of ten-fold cross validation were conducted and then means and sample standard deviations were computed. Our results show that for a specific data set it is essential to choose an appropriate discretization method since performance of discretization methods differ significantly. However, in general, among all of these discretization methods there is no statistically significant worst or best method. Thus, in practice, for a given data set the best discretization method should be selected individually. [ABSTRACT FROM AUTHOR]