Sujatha, R (2021) An efficient method for high performance prediction mechanism for diabetes using enhanced Firefly algorithm and Map-Reduce. Journal of Physics: Conference Series 1964 (2021) 042056. pp. 1-9. ISSN B2 and T Padma3

[thumbnail of sujatha2021.pdf] Text
sujatha2021.pdf - Published Version

Download (609kB)

Abstract

Algorithms in Data mining are utilized to predict unrefined data into useful
conventional information. This conservative information plays a vital role in the Health care
industry. In this study we focus on the functionalities of diabetes prediction. In diabetes data
we have the problem of data imbalance in predicting the accuracy. The Proposed tailored Firefly
Algorithm along with Map reduce is used to augment the efficacy and precision of prediction.
Comparison of Different bench mark algorithms with our new Extended Fire Fly is done and
variety of classification methods are used with moto to increase the effectiveness. The new
method helps to maximize the prediction of accuracy and reduces the time. The PIMA Indian
Diabetic Dataset from UCI machine learning repository is utilized for our experiment results.
Different metrics are used in order to prove the effectiveness.

Item Type: Article
Divisions: PSG College of Arts and Science > Department of Computer Science
Depositing User: Mr Team Mosys
Date Deposited: 26 Sep 2022 05:38
Last Modified: 26 Sep 2022 05:38
URI: http://ir.psgcas.ac.in/id/eprint/1541

Actions (login required)

View Item
View Item