Multifactor data analysis to forecast an individual's severity over novel COVID‐19 pandemic using extreme gradient boosting and random forest classifier algorithms.

MLA

Yenurkar, Ganesh Keshaorao, et al. “Multifactor Data Analysis to Forecast an Individual’s Severity over Novel COVID‐19 Pandemic Using Extreme Gradient Boosting and Random Forest Classifier Algorithms.” Engineering Reports, vol. 5, no. 12, Dec. 2023, pp. 1–18. EBSCOhost, https://doi.org/10.1002/eng2.12678.

APA

Yenurkar, G. K., Mal, S., Nyangaresi, V. O., Hedau, A., Hatwar, P., Rajurkar, S., & Khobragade, J. (2023). Multifactor data analysis to forecast an individual’s severity over novel COVID‐19 pandemic using extreme gradient boosting and random forest classifier algorithms. Engineering Reports, 5(12), 1–18. https://doi.org/10.1002/eng2.12678

Chicago

Yenurkar, Ganesh Keshaorao, Sandip Mal, Vincent O. Nyangaresi, Anshul Hedau, Prajwal Hatwar, Shreyas Rajurkar, and Juli Khobragade. 2023. “Multifactor Data Analysis to Forecast an Individual’s Severity over Novel COVID‐19 Pandemic Using Extreme Gradient Boosting and Random Forest Classifier Algorithms.” Engineering Reports 5 (12): 1–18. doi:10.1002/eng2.12678.