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Mortality Prediction of Countries
(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2018) Koç, Utku; Koç, Utku; 02.01. Department of Industrial Engineering; 02. Faculty of Engineering; 01. MEF University
In this study mortality reasons of countries detailed by sex and age-group is analyzed and different forecasting models are developed by using different machine learning algorithms. The dataset is obtained from the World Health Organization(WHO) Mortality Database. In WHO database there are different datasets for countries mortality reason number. The study used the dataset that used ICD-10 for classifying mortality reasons.ICD-10 is the 10 revision of International Statistical Classification of Diseases and Related Health Problems published by the World Health Organization. In addition to main mortality reason datasets, we add different independent variables and try to find the best features to fit models without biasing and overfitting and reaching high R2 and Mean Square Errors. To find the best model for forecasting mortality reasons by age-groups and sex different machine learning algorithms are fitted and results of these algorithms are analyzed.

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