Abstract
Diabetes mellitus (DM) has become one of the common disease in middle- and low-income countries. In the recent past, machine learning (ML) and data mining approach has been applied for prediction of diabetes with acceptable accuracy rate. A reliable diagnostic prediction system is thus desired by medical professionals. This paper highlights various machine learning algorithms for prediction of diabetes that include: Decision tree, random forest, Naïve Bayes, artificial neural network, support vector machine, and logistic regression, etc.
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Pradhan, G., Pradhan, R., Khandelwal, B. (2021). A Study on Various Machine Learning Algorithms Used for Prediction of Diabetes Mellitus. In: Borah, S., Pradhan, R., Dey, N., Gupta, P. (eds) Soft Computing Techniques and Applications. Advances in Intelligent Systems and Computing, vol 1248. Springer, Singapore. https://doi.org/10.1007/978-981-15-7394-1_50
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DOI: https://doi.org/10.1007/978-981-15-7394-1_50
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