Predicts the likelihood of Polycystic Ovary Syndrome based on patient attributes and symptoms
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-pcosDownload PCOS_data_without_infertility.xlsxOpen excel file and save as a CSV file under the same name Run program poetry run python pcos_predictor.py GitHub View Github
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