An effective approach for diabetic detection using supervised learning

Author:

Raymond V. Joseph,Priyadarshini K.,George Geogen

Publisher

AIP Publishing

Reference12 articles.

1. Uzer, Mustafa Serter, Nihat Yilmaz, and Onur Inan. "Feature selection method based on artificial bee colony algorithm and support vector machines for medical datasets classification." The Scientific World Journal 2013 (2013).

2. Lowongtrakool, Chaloemchai, and Nualsawat Hiransakolwong. "Noise filtering in unsupervised clustering using computation intelligence." International Journal of Math 6.59 (2012): 2911–2920.

3. Comparison of machine learning algorithms for the identification of acute exacerbations in chronic obstructive pulmonary disease

4. Kumari, V. Anuja, and R. Chitra. "Classification of diabetes disease using support vector machine." International Journal of Engineering Research and Applications 3.2 (2013): 1797–1801.

5. Iyer, Aiswarya, S. Jeyalatha, and Ronak Sumbaly. "Diagnosis of diabetes using classification mining techniques." arXiv preprint arXiv:1502.03774 (2015).

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