JIS College of Engineering, Department of Computer Science and Engineering, Students
Date Written: December 30, 2019
Abstract
This research paper has been made to get a better insight of diabetes and understand the factors responsible for diabetes in people by machine learning approaches. We have used machine learning to predict the accuracy of a person who can have diabetes based on some well understood factors. We have acquired datasets of various patients from the internet and analyzed their reports by structurally organizing the data and then applying various algorithms to predict the accuracy. This paper is aimed to give a better visualization of data and predict the possibility of a person to have diabetes in the future.
Keywords: Machine learning, Data Analysis, Decision Tree, Regression Techniques, Random Forest
Mitra, Debasree and Bhowmick, Arghya and Singh, Himanshu and Mondal, Dibya and Ansari, Khwaja Mohiuddin and Chakraborty, Kaustubh, Identification and Prediction of Factors Responsible for Diabetes by Machine Learning Approaches (December 30, 2019). 2nd International Conference on Non-Conventional Energy: Nanotechnology & Nanomaterials for Energy & Environment (ICNNEE) 2019, Available at SSRN: https://ssrn.com/abstract=3511644 or http://dx.doi.org/10.2139/ssrn.3511644
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