nahomfix / causal-inference

This project's aim is to classify a given breast mass data into Benign or Malignant using causal inference for selecting features.

Causal Inference

Overview

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.

Authors

• Nahom Bekele

Badges

Run Locally

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

License

MIT

causal-inference's Issues

Feature extraction and scaling

Exploratory Data Analysis

Track dataset with DVC

Treat missing values and outliers

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