COMPARISON OF DECISION TREE, NAÏVE BAYES, AND NEURAL NETWORK ALGORITHM FOR EARLY DETECTION OF DIABETES
نویسندگان
چکیده
منابع مشابه
Early Prediction of Gestational Diabetes Using Decision Tree and Artificial Neural Network Algorithms
Introduction: Gestational diabetes is associated with many short-term and long-term complications in mothers and newborns; hence, the detection of its risk factors can contribute to the timely diagnosis and prevention of relevant complications. The present study aimed to design and compare Gestational diabetes mellitus (GDM) prediction models using artificial intelligence algorithms. Materials ...
متن کاملComparison of gestational diabetes prediction with artificial neural network and decision tree models
Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural ne...
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In today world of internet, it is important to feedback the users based on what they demand. Moreover, one of the important tasks in data mining is classification. Today, there are several classification techniques in order to solve the classification problems like Genetic Algorithm, Decision Tree, Bayesian and others. In this article, it is attempted to classify researchers to “Expert” and “No...
متن کاملComparison of Decision Tree and Naïve Bayes Methods in Classification of Researcher’s Cognitive Styles in Academic Environment
In today world of internet, it is important to feedback the users based on what they demand. Moreover, one of the important tasks in data mining is classification. Today, there are several classification techniques in order to solve the classification problems like Genetic Algorithm, Decision Tree, Bayesian and others. In this article, it is attempted to classify researchers to “Expert” and “No...
متن کاملComparison of Gestational Diabetes Prediction Between Logistic Regression, Discriminant Analysis, Decision Tree and Artificial Neural Network Models
Background and Objectives: Gestational Diabetes Mellitus (GDM) is the most common metabolic disorder in pregnancy. In case of early detection, some of its complications can be prevented. The aim of this study was to investigate early prediction of GDM by logistic regression (LR), discriminant analysis (DA), decision tree (DT) and perceptron artificial neural network (ANN) and to compare these m...
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ژورنال
عنوان ژورنال: Jurnal Pilar Nusa Mandiri
سال: 2021
ISSN: 2527-6514,1978-1946
DOI: 10.33480/pilar.v17i1.2213