Open AccessGestational Diabetes Diagnosis with MSVM, MJ48 Classifier Models
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1040.0982s1119
Subject(s) - c4.5 algorithm , gestational diabetes , classifier (uml) , diabetes mellitus , computer science , artificial intelligence , machine learning , pregnancy , support vector machine , medicine , pattern recognition (psychology) , gestation , endocrinology , naive bayes classifier , biology , genetics
This paper focuses on designing an automated system for diagnosing gestational diabetes. Classification is one of the common predictive data mining tasks. It arranges the information and assembles a model to deliver the new grouped information. ‘Gestational diabetes mellitus’ (GDM) is a form of diabetes that occurs during pregnancy due to hormonal changes. Pregnant Women with GDM are at highest threat of future diabetes, especially type-2 diabetes. To diagnose the GDM, the two classifier models are proposed such as .Modified Support Vector Machine (MSVM) and Modified J48 (MJ48). Based on the performance analysis, the classifier model MJ48 provides more accuracy and less error rate than MSVM proposed classifier model