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Predicting Hypothyroid Disease using Ensemble Models through Machine Learning Approach

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    • Mohammed Ali Shaik, Praveen Pappula, T Sampath Kumar
,

Document Type : Research Article

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Abstract

In the present era most of the people are effected with hypothyroid disease. People who are of age 13 and above are more effected with this disease and day by day it is transforming into a dangerous disease. The prediction of disease at earlier stage is very crucial so superior treatment is contributed by doctors. In this paper, hypothyroid disease prediction is implemented through Ensemble Machine Learning Algorithms and through RapidMiner Tool. The algorithms like Random Forest, AdaBoost, and Gradient Boosting and Bagging are implemented. These models were compared and evaluated using evaluation metrics like Accuracy, Precision, and Recall. As multiple models are combined so ensemble method is more robust and accurate. It removes unrelated data in the medical dataset and produces accurate and precise data. It proves that the ensemble method is very efficient than using a single classifying method. Hence implementing the ensemble method, we can predict the patient’s disease efficiently

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European Journal of Molecular & Clinical Medicine
Volume 9, Issue 7
September 2022
Page 6738-6745
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  • Article View: 35
  • PDF Download: 50

APA

T Sampath Kumar, M. A. S. P. P. (2022). Predicting Hypothyroid Disease using Ensemble Models through Machine Learning Approach. European Journal of Molecular & Clinical Medicine, 9(7), 6738-6745.

MLA

Mohammed Ali Shaik, Praveen Pappula, T Sampath Kumar. "Predicting Hypothyroid Disease using Ensemble Models through Machine Learning Approach". European Journal of Molecular & Clinical Medicine, 9, 7, 2022, 6738-6745.

HARVARD

T Sampath Kumar, M. A. S. P. P. (2022). 'Predicting Hypothyroid Disease using Ensemble Models through Machine Learning Approach', European Journal of Molecular & Clinical Medicine, 9(7), pp. 6738-6745.

VANCOUVER

T Sampath Kumar, M. A. S. P. P. Predicting Hypothyroid Disease using Ensemble Models through Machine Learning Approach. European Journal of Molecular & Clinical Medicine, 2022; 9(7): 6738-6745.

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