Decision Trees in Large Data Sets

dc.contributor.authorÇetinkaya, Zeynep
dc.contributor.authorHorasan, Fahrettin
dc.date.accessioned2025-01-21T14:26:02Z
dc.date.available2025-01-21T14:26:02Z
dc.date.issued2021
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.
dc.identifier.dergipark763490
dc.identifier.doi10.29137/umagd.763490
dc.identifier.issn1308-5514
dc.identifier.issue1-140
dc.identifier.startpage151
dc.identifier.urihttps://dergipark.org.tr/tr/download/article-file/1186009
dc.identifier.urihttps://dergipark.org.tr/tr/pub/umagd/issue/59825/763490
dc.identifier.urihttps://doi.org/10.29137/umagd.763490
dc.identifier.urihttps://hdl.handle.net/20.500.12587/19826
dc.identifier.volume1
dc.language.isoen
dc.publisherKırıkkale Üniversitesi
dc.relation.ispartofUluslararası Mühendislik Araştırma ve Geliştirme Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectDecision trees
dc.subjectDecision tree algorithms
dc.subjectBig data sets
dc.subjectScalable decision trees
dc.subjectEngineering
dc.subjectMühendislik
dc.titleDecision Trees in Large Data Sets
dc.typeArticle

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