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  3. HR Analytics: Predicting Employee Churn in Python
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Exercise

Comparison of Employee attrition models

In this exercise, your task is to compare the balanced and imbalanced (default) models using the pruned tree (max_depth=7). The imbalanced model is already done using recall and ROC/AUC scores. Complete the same steps for the balanced model.

  • The variables features_train, target_train, features_test and target_test are already available in your workspace.
  • An imbalanced model has already been fit for you and, and its predictions saved as prediction.
  • The functions recall_score() and roc_auc_score() have been imported for you.

Instrukcje

100 XP
  • Initialize the balanced model, setting its maximum depth to 7, and its seed to 42.
  • Fit it to the training component using the training set.
  • Make predictions using the testing set.
  • Print the recall score and ROC/AUC score.