A Developed web-based software can easily fulfill the assumptions of correlation, classification and regression tasks in data processing

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dc.authoridARSLAN, Ahmet Kadir/0000-0001-8626-9542
dc.authoridYologlu, Saim/0000-0002-9619-3462
dc.authoridÇOLAK, CEMİL/0000-0001-5406-098X
dc.authorwosidARSLAN, Ahmet Kadir/AAA-2409-2020
dc.authorwosidYaşar, Şeyma/ABI-8055-2020
dc.authorwosidYologlu, Saim/ABI-8014-2020
dc.authorwosidÇOLAK, CEMİL/ABI-3261-2020
dc.contributor.authorYasar, Seyma
dc.contributor.authorArslan, A. Kadir
dc.contributor.authorColak, Cemil
dc.contributor.authorYologlu, Saim
dc.date.accessioned2024-08-04T20:46:55Z
dc.date.available2024-08-04T20:46:55Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.descriptionInternational Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEYen_US
dc.description.abstractThere are many assumptions that should be provided in regression and correlation analyses. If the assumptions are not met, the results of the analysis lead to errors. Multivariate regression analyses are performed by many software. However, many of this software are commercial and platform dependent. In this study, open source web-based software is developed to test the assumptions of simple/multiple linear regression, simple/multiple logistic regression analysis and correlation analysis, which are classification and regression techniques in machine learning. This software also provides a statistical interpretation of the results to researchers.en_US
dc.description.sponsorshipIEEE Turkey Sect,Anatolian Sci,Inonu Univ, Comp Sci Dept,Inonu Univ, Muhendisli Fakultesien_US
dc.identifier.scopus2-s2.0-85074886759en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11616/99038
dc.identifier.wosWOS:000591781100044en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2019 International Conference on Artificial Intelligence and Data Processing (Idap 2019)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLogistic regressionen_US
dc.subjectlinear regressionen_US
dc.subjectcorrelationen_US
dc.subjectopen source web-based softwareen_US
dc.titleA Developed web-based software can easily fulfill the assumptions of correlation, classification and regression tasks in data processingen_US
dc.typeConference Objecten_US

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