Instructions to use olivhult101/dvae26-project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use olivhult101/dvae26-project with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("olivhult101/dvae26-project", "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
Stroke Prediction model
This model predicts stroke based on features such as bmi, glucose level, age, etc.
Details
Features:
- Age
- Gender
- BMI
- Average glucose level
- Marital status
- Work type
- Heart disease
- Hypertension
- Smoking status
- Residence type
Target Feature: Stroke
Algorithm: Random Forest Classifier
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