%0 Journal Article
	%A Mehmet Hacibeyoglu and  Ahmet Arslan and  Sirzat Kahramanli
	%D 2011
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 54, 2011
	%T Improving Classification Accuracy with Discretization on Datasets Including Continuous Valued Features
	%U https://publications.waset.org/pdf/1314
	%V 54
	%X This study analyzes the effect of discretization on
classification of datasets including continuous valued features. Six
datasets from UCI which containing continuous valued features are
discretized with entropy-based discretization method. The
performance improvement between the dataset with original features
and the dataset with discretized features is compared with k-nearest
neighbors, Naive Bayes, C4.5 and CN2 data mining classification
algorithms. As the result the classification accuracies of the six
datasets are improved averagely by 1.71% to 12.31%.
	%P 623 - 626