Swalpa Kumar Roy

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

4. Results and Discussion 4.1. Accuracy Assessment of Classification Methods The predictive accuracy of both classifiers on the validation data is very high (see Table 5 and Table 6). We observed an F1-score of 0.99 for both RF and NN-based approach. The accuracy metrics indicated an apparent nearly perfect capability of both model types to differentiate between the DM-positive and the DM-negative class.