Predicting Type 2 Diabetes Based on Machine Learning - P. Moksha Sri Sai, G. Anuradha (International Journal of Advanced Science and Technology, 2020)
Now-a-days diabetes is being common in children and adults too. According to the growing mobility, in globe sugar victims will extend to 854 million, that process that two of the twenty grown-ups in upcoming is tolerating from sugar in 2060. To avoid this problem, we predict the recognition of diabetes is established on characteristic scrutiny. This can be done by the development of analysis aspect of the illness over the system of calculating demonstrative attribute and routine manner. To forecast the Type 2 Diabetes without commitment of pharmaceutical assessments over foretelling scrutiny. The proposed ML model used as foretelling Analysis permitted to recognize the best applicable method for the forecasting. The major algorithms used in this problem are Support vector machine, Random forest. By using these algorithms we can predict the risk factor before affecting the organs. Keywords: diabetes Miletus, Machine Learning, World health Organisation (WHO), Data Mining.