Tourism Package Prediction Model
Model Description
This is a GradientBoosting model trained to predict tourism package purchases based on customer behavior and demographics.
Model Performance
- Algorithm: GradientBoosting
- Task: Binary Classification
- Dataset: Tourism Customer Behavior
- Accuracy: 0.9443
Usage
import joblib
model = joblib.load('model.pkl')
predictions = model.predict(X)
Training Details
- MLflow experiment tracking
- Hyperparameter tuning with GridSearchCV
- 5-fold cross-validation
- Stratified train-test split
Features
The model uses customer demographics, interaction history, and behavioral features to predict travel package purchases.
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support