| Name | proxsurv JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | |
| Summary | Proximity Based Survival Analysis |
| upload_time | 2023-09-14 05:40:33 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | |
| 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.
|
| coveralls test coverage |
No coveralls.
|
# PBSA : Proximity Based Survival Analysis
Due to some uncertain cause we had to retract the package, this will bw made avaialble after December,2024.
[](https://pbsa.readthedocs.io/en/latest/?badge=latest)
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/](https://pbsa.readthedocs.io/en/latest/)
Raw data
{
"_id": null,
"home_page": "",
"name": "proxsurv",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "Proximity,Machine Learning,Survival Analysis,Ensemble Learning",
"author": "",
"author_email": "Rahul Goswami <yuvrajiro@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/47/02/12c309ecf1344ebf4cd570d55c1b4c910d51dacc87b2f98566182f66433e/proxsurv-0.0.3.tar.gz",
"platform": null,
"description": "\n\n\n\n\n# PBSA : Proximity Based Survival Analysis\n\nDue to some uncertain cause we had to retract the package, this will bw made avaialble after December,2024.\n\n[](https://pbsa.readthedocs.io/en/latest/?badge=latest)\n\n\n\n\n\n\n\n\n\nProximity Based Survival Analysis are algorithms, designed for survival prediction\nusing proximity information. The k-NN survival, Random Survival Forest, Kernel Survival\nare some examples of proximity based survival analysis. While this package tends \nto provide those algorithms later, currently the package provides the following algorithms:\n\n- COBRA Survival \n\nFor now other algorithms are taken from scikit-survival and np_survival to provide as\na base learner for the ensemble algorithms.\n\n## installation\n\n```\npip install proxsurv\n```\n\nThe documentation is available at [https://pbsa.readthedocs.io/en/latest/](https://pbsa.readthedocs.io/en/latest/)\n\n",
"bugtrack_url": null,
"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. ",
"summary": "Proximity Based Survival Analysis",
"version": "0.0.3",
"project_urls": null,
"split_keywords": [
"proximity",
"machine learning",
"survival analysis",
"ensemble learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "06e58de102a35a7aa95f99a689169b8efe3eb65fb6cee29780c78d6924c7dd3a",
"md5": "11108d0f9342a027e105cef6ad11176a",
"sha256": "92225cfe15d92e7b1c22eecfc17d0c5c1a390bc3d06face1ee8d4e984e32b653"
},
"downloads": -1,
"filename": "proxsurv-0.0.3-py3-none-any.whl",
"has_sig": false,
"md5_digest": "11108d0f9342a027e105cef6ad11176a",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 16023,
"upload_time": "2023-09-14T05:40:32",
"upload_time_iso_8601": "2023-09-14T05:40:32.027165Z",
"url": "https://files.pythonhosted.org/packages/06/e5/8de102a35a7aa95f99a689169b8efe3eb65fb6cee29780c78d6924c7dd3a/proxsurv-0.0.3-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "470212c309ecf1344ebf4cd570d55c1b4c910d51dacc87b2f98566182f66433e",
"md5": "ed2b446c6e16ffaefc422ab20da483d9",
"sha256": "af282d6025cc78489e6c2b017887d8c830cbdde2d51e653cd6d120c3a3e9a1b1"
},
"downloads": -1,
"filename": "proxsurv-0.0.3.tar.gz",
"has_sig": false,
"md5_digest": "ed2b446c6e16ffaefc422ab20da483d9",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 15117,
"upload_time": "2023-09-14T05:40:33",
"upload_time_iso_8601": "2023-09-14T05:40:33.101708Z",
"url": "https://files.pythonhosted.org/packages/47/02/12c309ecf1344ebf4cd570d55c1b4c910d51dacc87b2f98566182f66433e/proxsurv-0.0.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-09-14 05:40:33",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "proxsurv"
}
