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The main object of Human Resource Management using machine learning is to analyze employees' interest in their respective companies and make predictions about who will stay or leave the organization. The data is extracted using data scraping techniques and stored in CSV format. Data collected through this technique contains different features, and with the help of ML algorithms, it leads to predictions. This analysis helps the manager to make conclusions about who will stay or leave the organization; with this, the manager can approach a way to let stay a worthy employee in the organization. In our study, we used different techniques like feature scaling and SMOTE. According to the results, the suggested methods like random forest and XG boost classifier. The accuracy rate(%) values for the outcomes produced by the suggested methods will lead us to the conclusion. |
