Tourism Package Purchase Prediction Model
Model Description
This model predicts whether a customer will purchase the Wellness Tourism Package offered by "Visit with Us" travel company.
Model Type: Random Forest
Performance Metrics (Test Set)
- Accuracy: 0.9116
- Precision: 0.9216
- Recall: 0.5912
- F1-Score: 0.7203
- ROC-AUC: 0.9691
Best Hyperparameters
- criterion: gini
- max_depth: 20
- min_samples_leaf: 1
- min_samples_split: 2
- n_estimators: 150
Usage
from huggingface_hub import hf_hub_download
import joblib
# Download the model
model_path = hf_hub_download(
repo_id="vinayjags/tourism-model",
filename="best_tourism_model.pkl",
repo_type="model"
)
# Load the model
model = joblib.load(model_path)
# Make predictions
predictions = model.predict(X)
Training Details
- Training Samples: 3302
- Testing Samples: 826
- Number of Features: 29
- Random State: 42
Model Card Authors
This model was developed as part of an MLOps project for tourism package prediction.
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