پديدآورندگان :
khayamnia Monire Ph.D. candidate of Applied Mathematics, Tehran Payame Noor University, Tehran, Iran , Yazdchi Mohammadreza Associate Professor, Department of Biomedical Engineering , Faculty of Engineering , University of Isfahan, Isfahan, Iran , Heidari Aghile Associate Professor, Department of Mathematics, School of Mathematics, Mashhad Payame Noor University, Mashhad,Iran
كليدواژه :
Data mining , Naive , Bayes , Decision Tree , Random Decision Forest.
چكيده فارسي :
Data mining is an essential process, where intelligent methods are applied to extract data patterns, and it is the process of discovering interesting patterns and knowledge from large amount of data. In wide range of medical fields, it has been greatly expanded in recent years. This paper was designed to use three algorithms in the data mining field for recognition of migraine headache. Decision Tree, Naive-Bayes classification and Random Decision Forest techniques are used for migraine diagnosis. Performance of these techniques has been compared and Random Forest technique is observed as the best diagnosis with 93.1% accuracy.
