| Name | pairwiseprediction JSON |
| Version |
0.240311.7
JSON |
| download |
| home_page | |
| Summary | Handle a regression problem inducing the model on pairs A,B of instances |
| upload_time | 2024-03-13 04:55:39 |
| maintainer | |
| docs_url | None |
| author | davips |
| requires_python | >=3.10,<4.0 |
| license | |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://codecov.io/gh/davips/pairwiseprediction)
<a href="https://pypi.org/project/pairwiseprediction">
<img src="https://img.shields.io/pypi/v/pairwiseprediction.svg?label=release&color=blue&style=flat-square" alt="pypi">
</a>
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://davips.github.io/pairwiseprediction)
[](https://pepy.tech/project/pairwiseprediction)
# pairwiseprediction
[Latest Release](https://pypi.org/project/pairwiseprediction) |
[Current Code](https://github.com/davips/pairwiseprediction) |
[API Documentation](https://davips.github.io/pairwiseprediction)
---
Handle a regression problem inducing the model on pairs A,B of instances.
Last column of `X` is the continuous target. `y` is ignored.
Four modes are hipotetically possible, although only mode 'b' below is provided by now to ease compatibility with sklearn:
* a classification algorithm is trained to tell when instance A has higher target than instance B
* 1) the prediction is based on interpolation which is the type of result expected from a regression
* 2) the interpolated value can be converted to a hard prediction through binarization
* a regression algorithm is trained to predict the difference between target values of A,B
* 3) the prediction is the value provided directly by the regressor
* 4) the regression value can be converted to a hard prediction through binarization
Raw data
{
"_id": null,
"home_page": "",
"name": "pairwiseprediction",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.10,<4.0",
"maintainer_email": "",
"keywords": "",
"author": "davips",
"author_email": "dpsabc@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/a8/47/1968402b8f1e8e63d4c406d84656c20f4c12cfdcb8782f0d1c18f59fbfb1/pairwiseprediction-0.240311.7.tar.gz",
"platform": null,
"description": "\n[](https://codecov.io/gh/davips/pairwiseprediction)\n<a href=\"https://pypi.org/project/pairwiseprediction\">\n<img src=\"https://img.shields.io/pypi/v/pairwiseprediction.svg?label=release&color=blue&style=flat-square\" alt=\"pypi\">\n</a>\n\n[](https://www.gnu.org/licenses/gpl-3.0)\n\n[](https://davips.github.io/pairwiseprediction)\n[](https://pepy.tech/project/pairwiseprediction)\n\n\n# pairwiseprediction\n[Latest Release](https://pypi.org/project/pairwiseprediction) |\n[Current Code](https://github.com/davips/pairwiseprediction) |\n[API Documentation](https://davips.github.io/pairwiseprediction)\n\n---\n\n\nHandle a regression problem inducing the model on pairs A,B of instances.\n\nLast column of `X` is the continuous target. `y` is ignored.\n\nFour modes are hipotetically possible, although only mode 'b' below is provided by now to ease compatibility with sklearn:\n* a classification algorithm is trained to tell when instance A has higher target than instance B\n * 1) the prediction is based on interpolation which is the type of result expected from a regression\n * 2) the interpolated value can be converted to a hard prediction through binarization\n* a regression algorithm is trained to predict the difference between target values of A,B\n * 3) the prediction is the value provided directly by the regressor\n * 4) the regression value can be converted to a hard prediction through binarization\n",
"bugtrack_url": null,
"license": "",
"summary": "Handle a regression problem inducing the model on pairs A,B of instances",
"version": "0.240311.7",
"project_urls": null,
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "c5a4a4ab4b5998fefa153d8e957aede448faacce1e38bf8c65c38bc4350f6488",
"md5": "bac7010a3aa95b6e7c5fec499cc026bc",
"sha256": "5e16c0e3f73f583532136d473f574dc1de71f270cb31e62e1c70c0d313a7d709"
},
"downloads": -1,
"filename": "pairwiseprediction-0.240311.7-py3-none-any.whl",
"has_sig": false,
"md5_digest": "bac7010a3aa95b6e7c5fec499cc026bc",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10,<4.0",
"size": 9388,
"upload_time": "2024-03-13T04:55:34",
"upload_time_iso_8601": "2024-03-13T04:55:34.794210Z",
"url": "https://files.pythonhosted.org/packages/c5/a4/a4ab4b5998fefa153d8e957aede448faacce1e38bf8c65c38bc4350f6488/pairwiseprediction-0.240311.7-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "a8471968402b8f1e8e63d4c406d84656c20f4c12cfdcb8782f0d1c18f59fbfb1",
"md5": "9d791fa8cedb05b9f0e67b6dd7f36196",
"sha256": "d686d5653b33540e77ff1a1ee038fe754d284ec8a76d8a3b19494358b0ef44d7"
},
"downloads": -1,
"filename": "pairwiseprediction-0.240311.7.tar.gz",
"has_sig": false,
"md5_digest": "9d791fa8cedb05b9f0e67b6dd7f36196",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10,<4.0",
"size": 8076,
"upload_time": "2024-03-13T04:55:39",
"upload_time_iso_8601": "2024-03-13T04:55:39.290262Z",
"url": "https://files.pythonhosted.org/packages/a8/47/1968402b8f1e8e63d4c406d84656c20f4c12cfdcb8782f0d1c18f59fbfb1/pairwiseprediction-0.240311.7.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-03-13 04:55:39",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "pairwiseprediction"
}
