Random Survival Forest
The Random Survival Forest package provides a python implementation of the survival prediction method originally published by Ishwaran et al. (2008).
Reference: Ishwaran, H., Kogalur, U. B., Blackstone, E. H., & Lauer, M. S. (2008). Random survival forests. The annals of applied statistics, 2(3), 841-860.
Installation
$ pip install random-survival-forest
Contribute
Getting Started
>>> from random_survival_forest import RandomSurvivalForest
>>> timeline = range(0, 10, 1)
>>> rsf = RandomSurvivalForest(n_estimators=20, timeline=timeline)
>>> rsf.fit(X, y)
>>> round(rsf.oob_score, 3)
0.76
>>> y_pred = rsf.predict(X_val)
>>> c_val = concordance_index(y_val["time"], y_pred, y_val["event"])
>>> round(c_val, 3)
0.72
Support
If you are having issues or feedback, please let me know.
julian.spaeth@student.uni-tuebinden.de
License
MIT
1 maintainer
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