Research Paper
Year: 2023 | Month: April-June | Volume: 8 | Issue: 2 | Pages: 329-333
DOI: https://doi.org/10.52403/ijshr.20230242
Machine Learning for Forecasting Promotions
Pritam Ahire1, Atish Agale2, Mayur Augad3
1Associate professor, Department of Computer Engineering, Nutan Maharashtra Institute of Engineering and Technology, Pune university, pune India
2Under Graduate Student, Computer Engineering, Nutan Maharashtra Institute of Engineering and Technology, Pune university, pune, India
3Under Graduate Student, Computer Engineering, Nutan Maharashtra Institute of Engineering and Technology, Pune university, pune, India
Corresponding Author: Pritam Ahire
ABSTRACT
Employee promotion is an important aspect of an employee's career growth and job satisfaction. Organizations need to ensure that the promotion process is fair and unbiased. However, the promotion process can be complicated, and many factors need to be considered before deciding on a promotion. The use of data analytics and machine learning algorithms has become increasingly popular in recent years, and organizations can leverage these tools to predict employee promotion. In this paper, we present a web-based application for employee promotion prediction that uses the Naive Bayes algorithm. Our application uses data from employees and trains a Naive Bayes algorithm to predict employee promotion. We use Spyder Python libraries for data analysis and machine learning and a dB SQLite database for login and data storage.
[1] You can refer paper no 1 in the reference for more theory explanation regarding this project.
Keywords: [classification, machine Learning, Prediction, Confusion matrix, Naive bayes algorithm, attributes].