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Paper Details

Paper Title
Classification and Prediction of Diabetics using Weka and Hive Tool
Data mining is one such field which tries to extract some interesting facts from huge data set. Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by various data logging methods raises more challenges. The objective of this project is to train historical diabetes data and classifies them. Classifiers like Naïve Bayes, Decision Tree, Decision Stump, K star and Random forest algorithms are trained very efficiently in a supervised learning setting. Though the chosen dataset is small in size, to learn the big data tools and to find the effectiveness of the tools on a small data set Hadoop and Hive is used in this paper.
Classification, Diabetics, Big data, Hadoop, Hive
Others Details
Paper Id : 92432
Author Name : Dr.C.S.Kanimozhi Selvi
Co-Author Name(s) : Dr.S.V.KogilavaniDr.S.MalligaD.Jayaprakash
Volume/Issue No : Volume 05 Issue 04
Page No : 105-111
DOI Number : DOI:10.21090/IJAERD.92432
Publication Date : 2018-04-06
License : This work is licensed under a Creative Commons Attribution 4.0 International License.
website :
Impact Factor : 4.72, SJIF-2016
ISSN Details : eISSN: 2348-4470, pISSN:2348-6406