mini-causal 0.1.5

A mini package using causal inference for machine learning models

MiniCausal

Examples for Mini Causal

This folder contains runnable Jupyter notebooks demonstrating mini_causal features.

Notebooks included

• causal_models_classifier_example.ipynb — shows how to compare two classification models using mini_causal.causality.
• mini_causal_causal_counterfactual_example.ipynb — demonstrates the causal_counter counterfactual workflow.
• mini_causal_prostate_with_partial_counterfactual..ipynb — example using partial_counter on the prostate dataset.

Quick start

1. Create and activate a virtual environment (Windows PowerShell example):

python -m venv .venv
.\.venv\Scripts\Activate.ps1

2. Install dependencies for running the examples (see examples/requirements.txt):

python -m pip install -r examples/requirements.txt

3. Start Jupyter Lab or Notebook and open the example notebooks:

jupyter lab
# or
jupyter notebook

Notes

• The package expects standard data science libraries (NumPy, Pandas, SciPy, scikit-learn).
• If you run the notebooks from the repository root, ensure mini_causal is importable (install editable):

pip install -e .