Hacibeyoglu M.Arslan A.Kahramanli S.2020-03-262020-03-2620112010376Xhttps://hdl.handle.net/20.500.12395/27245This 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%.eninfo:eu-repo/semantics/closedAccessData mining classification algorithmsEntropy-based discretization methodArticle78555558N/A