To analyze attrition effectively, focus on these common data categories: Age, Gender, Marital Status.
Addressing attrition in employees who have been in the same role for more than 3 years. To help you with a more specific guide,
Attrition datasets are usually imbalanced (more people stay than leave). Use techniques like SMOTE (Synthetic Minority Over-sampling Technique) to balance the classes. Algorithm Selection: Logistic Regression: Good for baseline interpretability.
To analyze attrition effectively, focus on these common data categories: Age, Gender, Marital Status.
Addressing attrition in employees who have been in the same role for more than 3 years. To help you with a more specific guide,
Attrition datasets are usually imbalanced (more people stay than leave). Use techniques like SMOTE (Synthetic Minority Over-sampling Technique) to balance the classes. Algorithm Selection: Logistic Regression: Good for baseline interpretability.