Breast cancer is the second leading cause of death among women worldwide. In 2019, 268,600 new cases of invasive breast cancer were expected to be diagnosed in women in the U.S, along with 62,930 new cases of non-invasive breast cancer. Early detection is the best way to increase the chance of treatment and survivability. Machine learning has become a popular tool for assessing tumor behavior. This project's aim is to classify a given breast mass data into Benign or Malignant using causal inference for selecting features.
Clone the project
git clone https://github.com/nahomfix/causal-inference.git
Go to the project directory
cd causal-inference
Install dependencies
pip install -r requirements.txt