Instructions to use Satyanjay/Tourism_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Satyanjay/Tourism_Model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Satyanjay/Tourism_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
metadata
language: en
tags:
- machine-learning
- classification
- sklearn
- random-forest
- mlops
license: mit
datasets:
- Satyanjay/Tourism_Project_Processed
metrics:
- accuracy
Tourism Purchase Prediction Model
Overview
This model predicts whether a customer will purchase the Wellness Tourism Package.
Model Details
- Algorithm: Random Forest Classifier
- Framework: Scikit-learn
- Experiment Tracking: MLflow
Performance
- Accuracy: 0.897
- Recall (Class 1): 0.52
Dataset
- Satyanjay/Tourism_Project_Processed
Usage
Use huggingface_hub to download and load the model.