ModelOriented/survex
Explainable Machine Learning in Survival Analysis
This tool helps researchers and analysts understand why certain machine learning models predict specific 'time-to-event' outcomes, like patient survival or equipment failure. It takes complex survival analysis models and their data, then reveals the most influential factors driving their predictions. Healthcare professionals, reliability engineers, and actuaries can use this to gain insights into model behavior.
117 stars. No commits in the last 6 months.
Use this if you need to understand the individual factors contributing to predictions from complex survival analysis models, rather than just knowing the prediction itself.
Not ideal if you are only interested in simple, inherently interpretable survival models or do not require detailed explanations of model predictions.
Stars
117
Forks
10
Language
R
License
GPL-3.0
Category
Last pushed
Jun 15, 2024
Commits (30d)
0
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