Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/14844
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DC FieldValueLanguage
dc.rights.licenseBY-NC-ND-
dc.contributor.authorRadenković, Milica-
dc.date.accessioned2022-09-13T08:49:23Z-
dc.date.available2022-09-13T08:49:23Z-
dc.date.issued2022-
dc.identifier.isbn9788677762629en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/14844-
dc.description.abstractThe term data mining itself implies mining, i.e. the process of sorting, organizing or grouping a large amount of data, which enables the extraction of relevant information. More precisely, data mining leads to flexibility in data, discovery of relationships, regularity, legality and other structures where data can be organized into databases or can be textual, unstructured, derived from the Internet or data organized into time series. A significant change was made in the Bologna process with the introduction of doctoral studies, whose primary goal was to realize the link between education and research. As doctoral studies represent an important level of education, this paper is based on determining gender differences as determinants of the number of doctoral students in the Republic of Serbia. After downloading and installing the NCSS software tool, the downloading, transformation and preprocessing of data originating from the open data portal began. The result of this research is the analysis of data through regression methods, where the given regression mining technique with its set of methods made it possible to predict trends in gender differences as determinants of the number of doctors of science in the Republic of Serbia. The conducted research opens many possibilities for further research.en_US
dc.language.isoenen_US
dc.publisherUniversity of Kragujevac, Faculty od Technical Sciences, Čačaken_US
dc.rightsopenAccess-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.sourceProceedings TIE 2022 9th International Scientific Conference Technics and Informatics in Educationen_US
dc.subjectminingen_US
dc.subjectregressionen_US
dc.subjectdoctoral students in the Republic of Serbiaen_US
dc.subjectgenderen_US
dc.titleDetermining the number of doctoral students in the Republic of Serbia using regression algorithmen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisheden_US
dc.identifier.doi10.46793/TIE22.251Ren_US
dc.relation.conference“Technics and Informatics in Education – TIE 2022”en_US
dc.type.versionPublishedVersionen_US
Appears in Collections:Faculty of Technical Sciences, Čačak

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