shijiabraham/insurance-predictor

Insurance Charges Predictor

Predicts medical insurance charges using age, sex, BMI, number of children, smoking status and region.

How it works

The model uses linear regression. Sex and smoking status are converted to binary values, while region is one-hot encoded. The input features are standardized using StandardScaler before prediction.

The model achieved an R2 score of 0.8069 on the test data.

How to load it

from huggingface_hub import hf_hub_download
import joblib

path = hf_hub_download(
    "shijiabraham/insurance-predictor",
    "insurance_predictor.joblib"
)

model = joblib.load(path)

model.predict_charges(
    age=35,
    sex="Female",
    bmi=25,
    children=1,
    smoker="No",
    region="Northeast"
)