Instructions to use tina1210/visit-with-us-wellness-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use tina1210/visit-with-us-wellness-model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("tina1210/visit-with-us-wellness-model", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Visit with Us โ Wellness Package Purchase Predictor
This repository contains the best-performing trained model pipeline (preprocessing + RandomForestClassifier) to predict whether a customer will purchase the Wellness Tourism Package (ProdTaken).
Files
best_model.joblib: serialized sklearn Pipeline (preprocess + model)metrics.json: evaluation metrics on the held-out test setconfusion_matrix.json: confusion matrix on the held-out test set