A.A.S. Aldrawi

Work place: Department of Material Science and Engineering, Kastamonu University, Kastamonu, Turkey

E-mail: abcydrawi@gmail.com


Research Interests: Materials Science, Computational Science and Engineering, Data Structures and Algorithms


Abdusalam Ahmed Salem Aldrawi, He graduates and obtained the B.Sc. Degree in Data Analysis and computer science in 2012 at EL-Merghep University faculty of Economics and Commerce, and now student in master degree program in Kastamonu university institute of sciences Materials science and Engineering Department.

Author Articles
Evaluation of Different Machine Learning Methods for Caesarean Data Classification

By O.S.S. Alsharif K.M. Elbayoudi A.A.S. Aldrawi K. Akyol

DOI: https://doi.org/10.5815/ijieeb.2019.05.03, Pub. Date: 8 Sep. 2019

Recently, a new dataset has been introduced about the caesarean data. In this paper, the caesarean data was classified with five different algorithms; Support Vector Machine, K Nearest Neighbours, Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. The dataset is retrieved from California University website. The main objective of this study is to compare selected algorithms’ performances. This study has shown that the best accuracy that was for Naïve Bayes while the highest sensitivity which was for Support Vector Machine.

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