QLDT+ — Interpretable Quantum‑Logic Decision Trees

Code for building and evaluating QLDT+ trees (quantum‑logic inspired decision trees) and CART baselines on public datasets (Pima, Transfusion, Heart).

Quickstart

0) Prerequisites

• Python 3.10–3.11
• Graphviz runtime for PNG export

1) Create environment

# conda
conda env create -f environment.yml
conda activate qldt

# or pip
python -m venv .venv
# Windows: .venv\Scripts\activate
source .venv/bin/activate
pip install -r requirements.txt

2) Get data

Either put original CSVs into data/raw/ using these exact names:

• pima-indians-diabetes.data.csv
• transfusion.csv
• heart.csv

or run the fetcher:

python scripts/fetch_data.py --all

3) Run a demo

python src/run_qldt.py --dataset pima --grid --draw
python src/run_qldt.py --dataset transfusion --draw
python src/run_qldt.py --dataset heart --draw

Outputs appear in artifacts/:

• qldt_*.png, cart_*.png
• qldt_param_grid_search_results.csv
• qldt_interpretability_table.html
• qldt_feature_importance.png

Project layout

QLDT-Plus/
├─ src/
│  ├─ qldtplus.py
│  ├─ run_qldt.py
│  ├─ utils_io.py
│  └─__init__.py
├─ data/
│  ├─ sample/   # tiny csvs (optional)
│  └─ raw/      # full datasets (gitignored)
├─ artifacts/   # figures/csv/html outputs
├─ scripts/
│  └─ fetch_data.py
├─ tests/
│  └─ test_smoke.py
├─ environment.yml
├─ requirements.txt
├─ .gitignore
├─ .gitattributes        # (Git LFS)
└─ README.md

Reproducibility

• Fixed random seeds where applicable.
• Balanced splits.
• Regenerates all figures with the commands above.

License

This project is released under the MIT License (Simplified Attribution Version).
© 2025 Zahra Sheikh Najdi

You are free to use, modify, and distribute this software,
provided that proper credit is given to the author:

"Developed by Zahra Sheikh Najdi (2025)"

See the LICENSE file for full details.