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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file random_survival_forest-0.5.1.tar.gz.
File metadata
- Download URL: random_survival_forest-0.5.1.tar.gz
- Upload date:
- Size: 6.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6392befdf87fc16b25434851844c35e53bfd2cc515d725b5081172500e0eeccb
|
|
| MD5 |
c55cbc8aa826ac4df0ea034e4420c04a
|
|
| BLAKE2b-256 |
7a2888ec66a1d952d73c88b4372fe8d4fedeb6a694d038dde47fe3524513145a
|
