# 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.