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LaplacianNB is a Python module developed at Novartis AG for Naive Bayes classifier for laplacian modified models based on scikit-learn Naive Bayes implementation.
This classifier is suitable for binary/boolean data as it uses for prediction only indices of the positive bits. The algorithm was first implemented in Pipeline Pilot and KNIME.
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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Huge thanks to Florian Nigsch ([email protected]) for the first implementation of the algorithm in python and Peter Kutchukian ([email protected]) for scientific guidance and validation.
Author and maintainer: Bartosz Baranowski ([email protected])
Dependencies:
- Python (>= 3.8)
- pandas (>=1.4.2)
- numpy (>=1.22.4)
- scikit-learn (>=1.1.1)
- scipy (>=1.8.1)
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User installation:
pip install laplaciannb
v0.5.0 - Initial release