Kumar, P.; Gaikwad, S.B.; Ramya, S.T.; Tiwari, T.; Tiwari, M.; Kumar, B.
Predicting Employee Turnover: A Systematic Machine Learning Approach for Resource Conservation and Workforce Stability. Eng. Proc. 2023, 59, 117.
https://doi.org/10.3390/engproc2023059117
AMA Style
Kumar P, Gaikwad SB, Ramya ST, Tiwari T, Tiwari M, Kumar B.
Predicting Employee Turnover: A Systematic Machine Learning Approach for Resource Conservation and Workforce Stability. Engineering Proceedings. 2023; 59(1):117.
https://doi.org/10.3390/engproc2023059117
Chicago/Turabian Style
Kumar, Parmod, Sagar Balu Gaikwad, Shunmugavel Thanga Ramya, Tripti Tiwari, Mohit Tiwari, and Binod Kumar.
2023. "Predicting Employee Turnover: A Systematic Machine Learning Approach for Resource Conservation and Workforce Stability" Engineering Proceedings 59, no. 1: 117.
https://doi.org/10.3390/engproc2023059117
APA Style
Kumar, P., Gaikwad, S. B., Ramya, S. T., Tiwari, T., Tiwari, M., & Kumar, B.
(2023). Predicting Employee Turnover: A Systematic Machine Learning Approach for Resource Conservation and Workforce Stability. Engineering Proceedings, 59(1), 117.
https://doi.org/10.3390/engproc2023059117
