Proximity Based Survival Analysis
Project description
PBSA : Proximity Based Survival Analysis
Due to some uncertain cause we had to retract the package, this will bw made avaialble after December,2024.
Proximity Based Survival Analysis are algorithms, designed for survival prediction using proximity information. The k-NN survival, Random Survival Forest, Kernel Survival are some examples of proximity based survival analysis. While this package tends to provide those algorithms later, currently the package provides the following algorithms:
- COBRA Survival
For now other algorithms are taken from scikit-survival and np_survival to provide as a base learner for the ensemble algorithms.
installation
pip install proxsurv
The documentation is available at https://pbsa.readthedocs.io/en/latest/
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file proxsurv-0.0.3.tar.gz.
File metadata
- Download URL: proxsurv-0.0.3.tar.gz
- Upload date:
- Size: 15.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | af282d6025cc78489e6c2b017887d8c830cbdde2d51e653cd6d120c3a3e9a1b1 |
|
| MD5 | ed2b446c6e16ffaefc422ab20da483d9 |
|
| BLAKE2b-256 | 470212c309ecf1344ebf4cd570d55c1b4c910d51dacc87b2f98566182f66433e |
File details
Details for the file proxsurv-0.0.3-py3-none-any.whl.
File metadata
- Download URL: proxsurv-0.0.3-py3-none-any.whl
- Upload date:
- Size: 16.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 92225cfe15d92e7b1c22eecfc17d0c5c1a390bc3d06face1ee8d4e984e32b653 |
|
| MD5 | 11108d0f9342a027e105cef6ad11176a |
|
| BLAKE2b-256 | 06e58de102a35a7aa95f99a689169b8efe3eb65fb6cee29780c78d6924c7dd3a |
