This is the original dataset used for analyzing employee attrition. It includes variables related to personal demographics, job roles, work environment, and performance metrics. The target variable is Attrition (Yes/No), which indicates whether an employee has left the company. This dataset was used for exploration, segmentation, and preparing the training and test sets.

This is the test dataset, comprising the remaining 20% of the original data. It was used to evaluate the trained model’s performance, including accuracy, precision, recall, and F1-score. Comparing results between the training and test sets helps assess the model’s generalization and check for overfitting.

This is the training dataset, created by splitting 80% of the original data. It was used to train the predictive decision tree model in BigML, helping the model learn relationships between input features (like OverTime, JobSatisfaction, and BusinessTravel) and the target variable (Attrition). This forms the basis for prediction and simulation.