| Name | cobsurv JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | |
| Summary | Cobra Ensemble for Conditional Survival |
| upload_time | 2023-09-14 07:13:34 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.10 |
| license | MIT License Copyright (c) 2023 Rahul Goswami Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
proximity
machine learning
survival analysis
ensemble learning
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# cobsurv : Cobra Ensemble for Conditional Survival
[](https://cobsurv.readthedocs.io/en/latest/?badge=latest)
Cobra Ensemble for Conditional Survival are algorithms, designed for survival prediction
using proximity information. The k-NN survival, Random Survival Forest, Kernel Survival
are some examples of Cobra Ensemble for Conditional Survival. 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 cobsurv
```
The documentation is available at [https://cobsurv.readthedocs.io/en/latest/](https://cobsurv.readthedocs.io/en/latest/)
## Citation
```
@misc{goswami2023areanorm,
title={Area-norm COBRA on Conditional Survival Prediction},
author={Rahul Goswami and Arabin Kr. Dey},
year={2023},
eprint={2309.00417},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```
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