Decision Trees in Large Data Sets

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Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi
Volume:13 Issue:1
Decision Trees in Large Data Sets

Decision Trees in Large Data Sets

Authors : Zeynep ÇETİNKAYA, Fahrettin HORASAN

Pages : 140-151

Doi:10.29137/umagd.763490

View : 43 | Download : 9

Publication Date : 2021-01-18

Article Type : Review Paper

Abstract :Data 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.
Keywords : Decision trees, Decision tree algorithms, Big data sets, Scalable decision trees

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