COMPARATIVE ANALYSIS OF DIABETES PATIENTS MEDICAL DATA USING SUPERVISED MACHINE LEARNING ALGORITHMS AN EDUCATIONAL APPROACH
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Suleyman Demirel University
Abstract
The comparative analysis has been performed on tree supervised machine
learning algorithms i.e., decision trees, logistic regression and multi layer
perceptron neural
network over Waikato Environment for Knowledge Analysis tool on medical data for patients
with two types of diabetes disorders. Diabetes Mellitus
refers to the metabolic disorder that
happens from malfunction in insulin secretion and action. It is characterized by
hyperglycemia.The diagnosis of diabetes is very important now days using various types of
techniques.The dataset has been obtained from UCI machine learning repository for Pima
Indian Diabetes patients. The purpose of the research study is to show the usage of different
machine learning algorithms and performance metrics for education al purposes in teaching
machine learning to students from information systems field in more efficient and non trivial
way. During the research the comparative analysis studies have been performed which revealed
that less complex algorithms can be used for disease diagnosis and possess better performance
when properly configured.
Description
Keywords
Diabetes Mellitus, Supervised Learning, Performance Analysis, Clinical Decision Support Systems
Citation
COMPARATIVE ANALYSIS OF DIABETES PATIENTS MEDICAL DATA USING SUPERVISED MACHINE LEARNING ALGORITHMS AN EDUCATIONAL APPROACH, ShamiluuluS., Djakbarova U., Latuta K.N., Baimuratov O.А.