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-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

View Github

 

 

 

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