A Survey on Classification and Prediction Techniques in Data Mining for Diabetes Mellitus

M. Uma Maheswari; Dr. J. G. R. Sathiaseelan; T. Padma Nivethitha

Title:
A Survey on Classification and Prediction Techniques in Data Mining for Diabetes Mellitus

Authors:
T. Padma Nivethitha | M. Uma Maheswari | Dr. J. G. R. Sathiaseelan
DOI:
https://doi.org/10.31142/ijtsrd15878

Cite This Article :

T. Padma Nivethitha | M. Uma Maheswari | Dr. J. G. R. Sathiaseelan "A Survey on Classification and Prediction Techniques in Data Mining for Diabetes Mellitus" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5, August 2018, pp.496-504, URL: https://www.ijtsrd.com/papers/ijtsrd15878.pdf

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Abstract :
The medical industry incredibly utilizes the data mining systems for different expectations and characterization. The substantial data repositories produced is subjected to different calculations to distinguish the examples in the data. The diabetic is the most undermining ailment with the end goal where millions of people suffers each year. In this paper the forecast of the diabetics is done by utilizing different procedures like classification and prediction techniques decision tree, Naive Bayes, Support vendor machine(SVM), clustering, K-Nearest Neighbour, K-means, K-medoids, Neural Networks, Association rule mining and Multilayer Preceptron have been examined broadly. It is seen from the examination that the Naïve Bayes and C4.5 algorithm system show to have better execution with satisfactory results.

Keywords :
Data Mining, Diabetes, Prediction, C4.5, Naïve Bayes.

Publication Details:

Unique Identification Number : IJTSRD15878

Published In : Volume-2 | Issue-5, August 2018

Page Number(s) : 496-504

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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