Predicts the likelihood of Polycystic Ovary Syndrome based on patient attributes and symptoms
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Predicts the likelihood of Polycystic Ovary Syndrome based on patient attributes and symptoms using Logistic Regression.
Clone the Repository
git clone https://github.com/smv5467/pcos-prediction
Add Dependencies with Poetry
If you don’t have poetry install with:
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
poetry install
Download Data
Retrieve data from Kaggle: https://www.kaggle.com/prasoonkottarathil/polycystic-ovary-syndrome-pcos
Download PCOS_data_without_infertility.xlsx
Open excel file and save as a CSV file under the same name
Run program
poetry run python pcos_predictor.py
GitHub