Heart Disease Prediction Model π«
π Model Overview
This model uses Logistic Regression to predict the risk of heart disease based on various health-related features.
π Training Data
The model was trained on a dataset containing patient health attributes, including:
- Age
- Cholesterol Level
- Blood Pressure
- Body Mass Index (BMI)
π How to Use the Model
You can download and use the model in Python as follows:
from huggingface_hub import hf_hub_download
import joblib
# Download the model
model_path = hf_hub_download(repo_id="Sarah0022/heart-disease-model", filename="heart_disease_model.pkl")
# Load the model using joblib
model = joblib.load(model_path)
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no library tag.