Sujatha, R An efficient method for high performance prediction mechanism for diabetes using enhanced Firefly algorithm and Map-Reduce. Journal of Physics: Conference Series. pp. 1-9.
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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: | 22 Jun 2022 08:52 |
| Last Modified: | 22 Jun 2022 08:52 |
| URI: | http://ir.psgcas.ac.in/id/eprint/1246 |
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