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tourism-package-prediction-model
reva-anand/tourism-package-prediction-model
tourism-package-prediction-model is a machine learning model from reva-anand. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Public
Updated Jul 20, 2026
Repo size
3 MB
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.pkl1.5 MB · 100%
At a glance
- Access
- Public
- Created
- Jul 18, 2026
- Updated
- Jul 20, 2026
- SHA
- 1c6724cc
Model card
From the Hugging Face model README
Tourism Package Prediction Model
Best Model
Gradient Boosting
Model Performance
| Metric | Value |
|---|---|
| Accuracy | 0.9203 |
| Precision | 0.9174 |
| Recall | 0.6452 |
| F1 Score | 0.7576 |
Best Hyperparameters
{'classifier__n_estimators': 100, 'classifier__max_depth': 7, 'classifier__learning_rate': 0.1}
Features
The model predicts whether a customer is likely to purchase a Wellness Tourism Package using customer demographic, travel, and behavioural attributes.
Preprocessing Pipeline
The model was trained using an Scikit-learn Pipeline consisting of:
- Missing Value Imputation
- One-Hot Encoding for categorical variables
- Standard Scaling for numerical variables
- Gradient Boosting Classifier
MLOps Workflow
- Dataset registered in Hugging Face Dataset Hub
- Model trained using Hyperparameter Tuning (RandomizedSearchCV)
- Best model selected based on evaluation metrics
- Model registered in Hugging Face Model Hub
- Ready for deployment in Hugging Face Spaces
- Created
- Jul 18, 2026
- Updated
- Jul 20, 2026