APA (7th ed.) Citation

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 (Hoboken, N.J.), 5(12), -n/a. https://doi.org/10.1002/eng2.12678

Chicago Style (17th ed.) Citation

Yenurkar, Ganesh Keshaorao, Sandip Mal, Vincent O. Nyangaresi, Anshul Hedau, Prajwal Hatwar, Shreyas Rajurkar, and Juli Khobragade. "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 (Hoboken, N.J.) 5, no. 12 (2023): -n/a. https://doi.org/10.1002/eng2.12678.

MLA (9th ed.) Citation

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 (Hoboken, N.J.), vol. 5, no. 12, 2023, pp. -n/a, https://doi.org/10.1002/eng2.12678.