Survey on Data Mining Classification Techniques to Predict Diabetes
Journal Title: Elysium Journal of Engineering Research and Management - Year 2017, Vol 4, Issue 4
Abstract
This paper surveys on Data mining classification methods on CPCSSN dataset to etect diabetes. Data mining serves as the main application area to derive meaningful information from the humongous data that is accessible everywhere. After extracting this information, we require to classify the future data based on the properties learnt from the old data. Machine learning processes are the greatest prevalently used technique to attain this. In this paper we will discuss about three major classification algorithms: J48 Decision tree, Bagging Aggregation and Ada boost. We would be looking into the pros and cons of using each of these for classifying data. Also some analysis based on the experiment performed and their respective results will be discussed along the paper.
Authors and Affiliations
Sathya Chandrasekaran, Dharmarajan K
Keywords
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