The Cuts Selection Method Based on Histogram Segmentation and Impact on Discretization Algorithms

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dc.citation.spage675
dc.citation.volume24
dc.contributor.authorOgnjenovic, Visnja
dc.contributor.authorBrtka, Vladimir
dc.contributor.authorStojanov, Jelena
dc.contributor.authorBrtka, Eleonora
dc.contributor.authorBerkovic, Ivana
dc.date.accessioned2023-05-15T12:25:24Z
dc.date.available2023-05-15T12:25:24Z
dc.date.issued2022
dc.description.abstractThe preprocessing of data is an important task in rough set theory as well as in Entropy. The discretization of data as part of the preprocessing of data is a very influential process. Is there a connection between the segmentation of the data histogram and data discretization? The authors propose a novel data segmentation technique based on a histogram with regard to the quality of a data discretization. The significance of a cut’s position has been researched on several groups of histograms. A data set reduct was observed with respect to the histogram type. Connections between the data histograms and cuts, reduct and the classification rules have been researched. The result is that the reduct attributes have a more irregular histogram than attributes out of the reduct. The following discretization algorithms were used: the entropy algorithm and the Maximal Discernibility algorithm developed in rough set theory. This article presents the Cuts Selection Method based on histogram segmentation, reduct of data and MD algorithm of discretization. An application on the selected database shows that the benefits of a selection of cuts relies on histogram segmentation. The results of the classification were compared with the results of the Naïve Bayes algorithm
dc.identifier.doi10.3390/e24050675
dc.identifier.urihttps://vaseljena.ues.rs.ba/handle/123456789/143
dc.language.isoen
dc.publisherMDPI
dc.sourceEntropy
dc.subjectdata discretization; groups of histograms; cuts; MD algorithm; entropy
dc.titleThe Cuts Selection Method Based on Histogram Segmentation and Impact on Discretization Algorithms
dc.typeArticle
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Саобраћајни факултет [Научни радови] / Faculty of Transport and Traffic Engineering [Scientific papers]