| # Model Card: Gradient Boosting | |
| ## Model Description | |
| This model is a Gradient Boosting Classifier trained to predict tourism package purchases. | |
| It has been tuned using GridSearchCV on a SMOTE-resampled training dataset to address class imbalance. | |
| ## Tuned Parameters | |
| - **Parameters**: {'learning_rate': 0.2, 'max_depth': 7, 'n_estimators': 300} | |
| ## Evaluation Metrics (on Test Set) | |
| * Accuracy: 0.9467 | |
| * Precision: 0.9389 | |
| * Recall: 0.7736 | |
| * F1-Score: 0.8483 | |
| * ROC AUC: 0.9771 | |
| ## Model Purpose | |
| This model aims to accurately predict whether a customer will take a tourism package, aiding in targeted marketing efforts and improving sales efficiency. | |
| ## Usage | |
| To use this model, load the `gradient_boosting_model.pkl` file and apply it to preprocessed data. Ensure the data undergoes the same preprocessing steps (column removal, outlier handling, one-hot encoding, and StandardScaler scaling) as the training data. | |