Breast cancer prediction using causal Inference.

Content

• Overview
• Dataset Description
• Install
• Project Structure

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Overview

The Dataset Description

• Diagnosis: The diagnosis of breast tissues (M = malignant, B = benign)
• Radius mean: mean of distances from center to points on the perimeter
• Texture mean: standard deviation of gray-scale values
• Perimeter_mean: mean size of the core tumor
• Area_mean
• Smoothness_mean: mean of local variation in radius lengths
• Compactness_mean: mean of $(perimeter^2 / area - 1.0)$
• Concavity_mean: mean of severity of concave portions of the contour
• concave points_mean: mean for number of concave portions of the contour

Install

clone https://github.com/Melak2017/Causality-Inference-
pip install -r requirements.txt

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Project Structure

.
├── .github/workflows              # github actions
├── .vscode                        # collection of folders that are opened in a VS Code window.
├── .dvc                           # for data versioning.
├── data                           # data directory
├── logs                           # log files
├── notebooks                      # directory contaning notebok files.
│   ├── causal_analysis.ipynb      # notebook containing causal infrerence explanatory analysis.
│   ├── data_analysis.ipynb        # notebook for explanatory data analysis of the dataset.
│   └── data_cleaning              # notebook for data cleaning and preparation.
│
├── screenshots                    # A sample screenshots of analysis result.
├── scripts                        # script files.
|    ├── data_cleaner.py           # a python script for cleaning pandas dataframes.
│    ├── data_loader.py            # a python script for loading csv and excel files to a dataframe.
│    ├── data_preview.py           # a python script for to geting information about the data.
│    ├── plots.py                  # a python script for plotting dataframes.
│    └── ScalarNormalizer.py       # a python script for normalizing model feature.
|
├── tests                          # directory for unit testing
|    └── test_get_preview.py       # unit-test file
├── requirements.txt               # a text file lsiting the projet's dependancies
├── .gitignore                     # files to ignore when committing
├── setup.py                       # a configuration file for installing the scripts as a package
├──LICENSE                         # license file
├── .dvcigonre                     # files to ignore when committing
└── README.md                      # Markdown text with explanation of the project and the structure.

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