Diabetes prediction by using Big Data Tool and Machine Learning Approaches

The use of big data in daily life is increasing from health care, social networks, banking systems, entry into the banking system, use of sensors and smart devices, leading to large amounts of data. That's why, it is necessary to develop a model and device that handles data in optimized form. In this paper, diabetes predicated from a data set with the help of various machine-learning algorithms such as Naive bayes, KNN algorithm, Random forest, logistic regression. The main objective of the paper is to observe diabetes disease with the help of big data tools and machine learning model. For doing this, the authors can select more accurate model with the help of some matrices. This paper predict diabetes disease using four machine learning models and then compare their performance among themselves. Machine learning provides more flexible and scalability than the older bio statistical method that helps it perform a variety of tasks such as risk detection, diagnosis, classification, and prediction.