Decision Trees in Large Data Sets

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dc.contributor.authorÇetinkaya, Zeynep
dc.date.accessioned2025-01-21T16:11:54Z
dc.date.available2025-01-21T16:11:54Z
dc.date.issued2021
dc.departmentKırıkkale Üniversitesi
dc.description.abstractData mining is the process of obtaining information, which is used to identify and define the relationships between data of different qualities. One of the important problems encountered in this process is the classification process in large data sets. Extensive research has been done to find solutions to this classification problem and different solution methods have been introduced. Some decision tree algorithms are among the structures that can be used effectively in this field. In this article, various decision tree structures and algorithms used for classification process in large data sets are discussed. Along with the definitions of the algorithms, the similarities and existing differences between them were determined, their advantages and disadvantages were investigated. Key Words
dc.identifier.doi10.29137/umagd.763490
dc.identifier.endpage151
dc.identifier.issn1308-5514
dc.identifier.issue1
dc.identifier.startpage140
dc.identifier.trdizinid1142931
dc.identifier.urihttps://doi.org/10.29137/umagd.763490
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1142931
dc.identifier.urihttps://hdl.handle.net/20.500.12587/21596
dc.identifier.volume13
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofUluslararası Mühendislik Araştırma ve Geliştirme Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectBilgisayar Bilimleri
dc.subjectYazılım Mühendisliği
dc.subjectMatematik
dc.subjectİstatistik ve Olasılık
dc.titleDecision Trees in Large Data Sets
dc.typeReview Article

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