Comparison of machine learning algorithms on different datasets

dc.contributor.author	UYSAL, Elif
dc.contributor.author	ÖZTÜRK, Ali
dc.date.accessioned	2020-08-07T12:52:36Z
dc.date.available	2020-08-07T12:52:36Z
dc.date.issued	2018
dc.identifier	10.1109/SIU.2018.8404193
dc.identifier.issn	9781538615010 (ISBN)
dc.identifier.uri	http://hdl.handle.net/20.500.12498/2862
dc.description.abstract	Machine learning algorithms are methods used to classify data. Aim of this study is comparison of machine learning algorithms on different datasets. For this study, 9 different machine learning algorithms with 10 fold cross validation method in WEKA is classified on 3 different datasets. As a result of classification, machine learning algorithm which has high accuracy rate is different for 3 datasets. Multilayer Perceptron algorithm for Car Evaluation dataset, Random Forest algorithm for Image Segmentation dataset and Simple Logistic algorithm for User Knowledge Modeling dataset were obtained. © 2018 IEEE.
dc.language.iso	Turkish
dc.publisher	Institute of Electrical and Electronics Engineers Inc.
dc.source	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
dc.subject	Veri Seti
dc.subject	Makine Öğrenmesi
dc.subject	Sınıflandırma
dc.subject	WEKA
dc.subject	Dataset
dc.subject	Machine Learning
dc.subject	Classification
dc.title	Comparison of machine learning algorithms on different datasets
dc.title.alternative	Makine Öğrenmesi Algoritmalarının Farklı Veri Setleri Üzerinde Karşılaştırılması
dc.type	Konferans Bildirisi