Beqiri, Lavdim and Velinov, Aleksandar and Fetaji, Bekim and Loku, Lindita and Buçuku , Agon and Zdravev, Zoran (2020) Analysis of Diabetes Dataset. In: MIPRO 2020, 43rd International Convention, 28 Sep - 02 Oct 2020, Opatija, Croatia.
Preview |
Text
MIPRO2020_paper.pdf Download (1MB) | Preview |
Abstract
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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Natural sciences > Computer and information sciences |
| Divisions: | Faculty of Computer Science |
| Depositing User: | Aleksandar Velinov |
| Date Deposited: | 07 Oct 2020 08:44 |
| Last Modified: | 17 Dec 2022 13:32 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/26616 |
Actions (login required)
 |
View Item |