An Interactive Web Tool for Classification Problems Based on Machine Learning Algorithms Using Java Programming Language: Data Classification Software

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dc.authorscopusid57200276428
dc.authorscopusid57211715604
dc.authorscopusid57188684428
dc.authorscopusid11738942300
dc.contributor.authorPercin I.
dc.contributor.authorYagin F.H.
dc.contributor.authorArslan A.K.
dc.contributor.authorColak C.
dc.date.accessioned2024-08-04T20:04:00Z
dc.date.available2024-08-04T20:04:00Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.description3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 -- 11 October 2019 through 13 October 2019 -- 156063en_US
dc.description.abstractClassification analysis is a frequently used approach in fields such as biomedical, bioinformatics, medical and engineering. In the field of health, it has become common to classify diseases based on risk factors by machine learning methods and to determine the effect sizes of these risk factors on the disease. There are many analysis tools used to guide researchers in classification analysis. While some of these tools are commercial and provide basic methods for classification analysis, some offer advanced analysis techniques and are desktop applications such as the WEKA environment.The WEKA environment includes comprehensive tools for classification analysis. However, use of the WEKA environment can be difficult and time-consuming, especially when a quick assessment is essential for users who do not have WEKA tool on their computer (doctors, etc.). Therefore; fast, comprehensive, free and easy to use analysis tool is required. The purpose of this study is to develop a user-friendly web tool (Data Classification Software; DCS) based on the classification algorithms of WEKA tool in Java programming language.The data classification software can be used on any device with an internet connection, which is independent of the any operating systems. In the developed web-based tool, data preprocessing module consists of missing value assignment, variable type conversion and normalization-standardization methods. Classification module encapsulates random forest, Naive Bayes, Bayes Network, j48, sequential minimal optimization, a rule and attribute selected classifier algorithms. This web tool can be accessed free of charge at http://biostatapps.inonu.edu.tr/DCS/. © 2019 IEEE.en_US
dc.identifier.doi10.1109/ISMSIT.2019.8932861
dc.identifier.isbn9781728137896
dc.identifier.scopus2-s2.0-85077975567en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISMSIT.2019.8932861
dc.identifier.urihttps://hdl.handle.net/11616/92254
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectclassificationen_US
dc.subjectensemble learningen_US
dc.subjectjavaen_US
dc.subjectmachine learningen_US
dc.titleAn Interactive Web Tool for Classification Problems Based on Machine Learning Algorithms Using Java Programming Language: Data Classification Softwareen_US
dc.typeConference Objecten_US

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