id: 05285118
dt: a
an: 05285118
au: Blajdo, Piotr; Grzymala-Busse, Jerzy W.; Hippe, Zdzislaw S.; Knap,
    Maksymilian; Mroczek, Teresa; Piatek, Lukasz
ti: A comparison of six approaches to discretization ‒ a rough set
    perspective.
so: Wang, Guoyin (ed.) et al., Rough sets and knowledge technology. Third
    international conference, RSKT 2008, Chengdu, China, May 17‒19, 2008.
    Proceedings. Berlin: Springer (ISBN 978-3-540-79720-3/pbk). Lecture
    Notes in Computer Science 5009. Lecture Notes in Artificial
    Intelligence, 31-38 (2008).
py: 2008
pu: Berlin: Springer
la: EN
cc: 
ut: Rough sets; Discretization; Cluster analysis; Merging intervals; Ten-fold
    cross validation; Test on the difference between means; F-test
ci: 
li: doi:10.1007/978-3-540-79721-0_10
ab: Summary: 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.
rv: