Scikit-Survival: A Library for Time-to-Event Analysis Built on Top of Scikit-Learn
Abstract
scikit-survival is an open-source Python package for time-to-event analysis fully compatible with scikit-learn. It provides implementations of many popular machine learning techniques for time-to-event analysis, including penalized Cox model, Random Survival Forest, and Survival Support Vector Machine. In addition, the library includes tools to evaluate model performance on censored time-to-event data. The documentation contains installation instructions, interactive notebooks, and a full description of the API. scikit-survival is distributed under the GPL-3 license with the source code and detailed instructions available at https://github.com/sebp/scikit-survival
Cite
Text
Pölsterl. "Scikit-Survival: A Library for Time-to-Event Analysis Built on Top of Scikit-Learn." Machine Learning Open Source Software, 2020.Markdown
[Pölsterl. "Scikit-Survival: A Library for Time-to-Event Analysis Built on Top of Scikit-Learn." Machine Learning Open Source Software, 2020.](https://mlanthology.org/mloss/2020/polsterl2020jmlr-scikitsurvival/)BibTeX
@article{polsterl2020jmlr-scikitsurvival,
title = {{Scikit-Survival: A Library for Time-to-Event Analysis Built on Top of Scikit-Learn}},
author = {Pölsterl, Sebastian},
journal = {Machine Learning Open Source Software},
year = {2020},
pages = {1-6},
volume = {21},
url = {https://mlanthology.org/mloss/2020/polsterl2020jmlr-scikitsurvival/}
}