laplaciannb 0.6.1

**LaplacianNB** is a Python module developed at **Novartis AG** for Naive Bayes classifier for laplacian modified models based on scikit-learn Naive Bayes implementation.

LaplacianNB

Naive Bayes classifier for Laplacian-modified models
Efficient, scikit-learn compatible, and designed for binary/boolean data

LaplacianNB is a Python module developed at Novartis AG for a Naive Bayes classifier for Laplacian-modified models, based on the scikit-learn Naive Bayes implementation.

This classifier is ideal for binary/boolean data, using only the indices of positive bits for efficient prediction. The algorithm was first implemented in Pipeline Pilot and KNIME.

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🚀 Features

• Naive Bayes classifier for Laplacian-modified models
• Optimized for binary/boolean data
• Fast prediction using indices of positive bits
• scikit-learn compatible API
• Lightweight and easy to integrate

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📦 Installation

Install the latest release from PyPI:

pip install laplaciannb

📚 Literature

Nidhi; Glick, M.; Davies, J. W.; Jenkins, J. L. Prediction of biological targets
for compounds using multiple-category Bayesian models trained on chemogenomics
databases. J. Chem. Inf. Model. 2006, 46, 1124– 1133,
https://doi.org/10.1021/ci060003g

Lam PY, Kutchukian P, Anand R, et al. Cyp1 inhibition prevents doxorubicin-induced cardiomyopathy
in a zebrafish heart-failure model. Chem Bio Chem. 2020:cbic.201900741.
https://doi.org/10.1002/cbic.201900741

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👤 Authors & Maintainers

• Bartosz Baranowski ([e-mail])
• Edgar Harutyunyan ([e-mail])

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📝 Changelog

• v0.6.1 - Fixes for scikit-learn 1.7, rdkit 2025+ compatibility, move to uv build
• v0.6.0 - Move to pdm build
• v0.5.0 - Initial release

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📄 License

This project is licensed under the BSD 3-Clause License. See the LICENSE file for details.