sebp/scikit-survival
Survival analysis built on top of scikit-learn
This tool helps researchers and analysts predict when an event will occur, like patient recovery or machine failure, even when some subjects haven't experienced the event yet. You input data with observed event times and censored data (where the event hasn't happened or wasn't observed within the study period), and it outputs models that estimate event probabilities over time. This is for data scientists, statisticians, and researchers working with time-to-event data.
1,282 stars. Used by 5 other packages. Actively maintained with 7 commits in the last 30 days. Available on PyPI.
Use this if you need to analyze time until an event, accounting for incomplete observations where the event has not yet occurred (censored data).
Not ideal if your data solely consists of binary outcomes (event occurred/did not occur) without any time component or censoring.
Stars
1,282
Forks
223
Language
Python
License
GPL-3.0
Category
Last pushed
Mar 11, 2026
Commits (30d)
7
Dependencies
8
Reverse dependents
5
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