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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 suitable for binary/boolean data as it uses only indices of the positive bits for prediction. The algorithm was first implemented in Pipeline Pilot and KNIME.
- Naive Bayes classifier for Laplacian modified models
- Suitable for binary/boolean data
- Efficient prediction using indices of positive bits
You can install the package using pip:
pip install laplaciannbNidhi; 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
Author and maintainer: Bartosz Baranowski ([email protected])
- Bartosz Baranowski ([email protected])
- Edgar Harutyunyan ([email protected])
v0.6.0- Move to pdm buildv0.5.0- Initial release
This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.