Analysis of Diabetes Dataset

摘要

The focus of the research study was analysis of diabetes dataset and how it will perform if we try to do a prediction of diabetes with different machine learning algorithms. We used the original dataset from the National Institute of Diabetes, and Digestive and Kidney Diseases. The dataset can be used to predict whether or not a patient has diabetes, based on certain diagnostics. For analysis we used Amazon Web Services. We used AWS S3 service to store our dataset, and Amazon Sagemaker to perform an analysis. For the given dataset we applied three classification models: Logistic Regression Model, K-nearest Neighbors and Support Vector Machines. For each of the models we also performed a performance measurement. We also compared all the results we got and according to the results, Support Vector Machines has the best performance. Insights and recommendations are provided.