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Paper Details
Paper Title
Analysis of various data mining classification techniques to predict diabetes mellitus
Authors
T.Nithyapriya, S.Dhinakaran
Abstract
Data mining approach helps to diagnose patient’s diseases. Diabetes Mellitus is a chronic disease to affect various organs of the human body. Early prediction can save human life and can take control over the diseases. This research work explores the early prediction of diabetes using various data mining techniques. The real time diabetic based dataset has taken with 203 instances for training data set and 52 instances for test data set to determine the accuracy of the Naïve Bayes, SVM and J48 classification techniques in prediction. The analysis proves that SVM Classifier provide the highest accuracy than other techniques.
Keywords- Data mining, Diabetes, Prediction, accuracy, classification
Publication Details
Unique Identification Number - IJEDR1704113Page Number(s) - 695-703Pubished in - Volume 5 | Issue 4 | November 2017DOI (Digital Object Identifier) - Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
T.Nithyapriya, S.Dhinakaran, "Analysis of various data mining classification techniques to predict diabetes mellitus", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 4, pp.695-703, November 2017, Available at :http://www.ijedr.org/papers/IJEDR1704113.pdf
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