Improved prediction of diabetes based on glucose levels in blood using data science algorithms

Abstract

In this paper, diabetes disease is predicted more accurately based on Glucose Levels in the blood of the person using Data Science Algorithms Logistic Regression, Decision Tree, Naive Bayes and K-Means Data Science Algorithms. The analysis is done based on 09 attributes and 399 observations. Finally, a comparative analysis is done for the results of above stated data science algorithms and the results with Logistic Regression Algorithm proved to be better with 80% accuracy.