| Name | felimination JSON |
| Version |
0.2.2
JSON |
| download |
| home_page | |
| Summary | This library contains some useful scikit-learn compatible classes for feature selection. |
| upload_time | 2024-01-15 12:37:36 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.7 |
| license | |
| keywords |
feature selection
scikit-learn
machine learning
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://github.com/ClaudioSalvatoreArcidiacono/felimination/actions?query=workflow%3A%22Tests%22)
[](#)
[](https://claudiosalvatorearcidiacono.github.io/felimination/)
# felimination
This library contains some useful scikit-learn compatible classes for feature selection.
## Features
- [Recursive Feature Elimination with Cross Validation using Permutation Importance](reference/RFE.md#felimination.rfe.PermutationImportanceRFECV)
## Requirements
- Python 3.7+
- NumPy
- Scikit-learn
- Pandas
## Installation
In a terminal shell run the following command
```
pip install felimination
```
## Usage
```python
from felimination.rfe import PermutationImportanceRFECV
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification
import numpy as np
X, y = make_classification(
n_samples=1000,
n_features=20,
n_informative=6,
n_redundant=10,
n_clusters_per_class=1,
random_state=42,
)
selector = PermutationImportanceRFECV(LogisticRegression(), step=0.3)
selector.fit(X, y)
selector.support_
# array([False, False, False, False, False, False, False, False, False,
# False, False, True, False, False, False, False, False, False,
# False, False])
selector.ranking_
# array([9, 3, 8, 9, 7, 8, 5, 6, 9, 6, 8, 1, 9, 7, 8, 9, 9, 2, 4, 7])
selector.plot()
```
It looks like `5` is a good number of features, we can set the number of features to select to 5 without need of retraining
```python
selector.set_n_features_to_select(5)
selector.support_
# array([False, True, False, False, False, False, True, False, False,
# False, False, True, False, False, False, False, False, True,
# True, False])
```
## License
This project is licensed under the BSD 3-Clause License - see the LICENSE.md file for details
## Acknowledgments
- [scikit-learn](https://scikit-learn.org/)
Raw data
{
"_id": null,
"home_page": "",
"name": "felimination",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "feature selection,scikit-learn,machine learning",
"author": "",
"author_email": "Claudio Salvatore Arcidiacono <author@email.com>",
"download_url": "https://files.pythonhosted.org/packages/46/1a/c067cd7fa4db99b74e4b997def4abb3cc25a22f8e0e8bf68ce01fbc9be30/felimination-0.2.2.tar.gz",
"platform": null,
"description": "[](https://github.com/ClaudioSalvatoreArcidiacono/felimination/actions?query=workflow%3A%22Tests%22)\n[](#)\n[](https://claudiosalvatorearcidiacono.github.io/felimination/)\n\n\n# felimination\n\nThis library contains some useful scikit-learn compatible classes for feature selection.\n\n## Features\n\n- [Recursive Feature Elimination with Cross Validation using Permutation Importance](reference/RFE.md#felimination.rfe.PermutationImportanceRFECV)\n\n## Requirements\n\n- Python 3.7+\n- NumPy\n- Scikit-learn\n- Pandas\n\n## Installation\n\nIn a terminal shell run the following command\n```\npip install felimination\n```\n\n## Usage\n\n```python\nfrom felimination.rfe import PermutationImportanceRFECV\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.datasets import make_classification\nimport numpy as np\n\n\nX, y = make_classification(\n n_samples=1000,\n n_features=20,\n n_informative=6,\n n_redundant=10,\n n_clusters_per_class=1,\n random_state=42,\n)\n\nselector = PermutationImportanceRFECV(LogisticRegression(), step=0.3)\n\nselector.fit(X, y)\n\nselector.support_\n# array([False, False, False, False, False, False, False, False, False,\n# False, False, True, False, False, False, False, False, False,\n# False, False])\n\nselector.ranking_\n# array([9, 3, 8, 9, 7, 8, 5, 6, 9, 6, 8, 1, 9, 7, 8, 9, 9, 2, 4, 7])\nselector.plot()\n```\n\n\nIt looks like `5` is a good number of features, we can set the number of features to select to 5 without need of retraining\n\n```python\nselector.set_n_features_to_select(5)\nselector.support_\n# array([False, True, False, False, False, False, True, False, False,\n# False, False, True, False, False, False, False, False, True,\n# True, False])\n```\n\n## License\n\nThis project is licensed under the BSD 3-Clause License - see the LICENSE.md file for details\n\n## Acknowledgments\n\n- [scikit-learn](https://scikit-learn.org/)\n\n",
"bugtrack_url": null,
"license": "",
"summary": "This library contains some useful scikit-learn compatible classes for feature selection.",
"version": "0.2.2",
"project_urls": {
"Bug Tracker": "https://github.com/ClaudioSalvatoreArcidiacono/felimination/issues",
"Documentation": "https://claudiosalvatorearcidiacono.github.io/felimination/",
"Homepage": "https://github.com/ClaudioSalvatoreArcidiacono/felimination"
},
"split_keywords": [
"feature selection",
"scikit-learn",
"machine learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "f22f27e70521d1db35f37d03a8e61954d939ecb5d9e4905562414830a0d1fec9",
"md5": "65b5a0cc08c0a8e178329fa602381369",
"sha256": "6610ffb9b135115ce572bd30fc2e686cc8342da54969b3b8ea48bebd73ded869"
},
"downloads": -1,
"filename": "felimination-0.2.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "65b5a0cc08c0a8e178329fa602381369",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 17409,
"upload_time": "2024-01-15T12:37:34",
"upload_time_iso_8601": "2024-01-15T12:37:34.552007Z",
"url": "https://files.pythonhosted.org/packages/f2/2f/27e70521d1db35f37d03a8e61954d939ecb5d9e4905562414830a0d1fec9/felimination-0.2.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "461ac067cd7fa4db99b74e4b997def4abb3cc25a22f8e0e8bf68ce01fbc9be30",
"md5": "c7f93c2de616b952e4d817f7d249f4af",
"sha256": "98f6b063b1c6b9e8b958ad885d9b6c4ec40a9e1ac7e27f564f53601d90bed14c"
},
"downloads": -1,
"filename": "felimination-0.2.2.tar.gz",
"has_sig": false,
"md5_digest": "c7f93c2de616b952e4d817f7d249f4af",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 14135,
"upload_time": "2024-01-15T12:37:36",
"upload_time_iso_8601": "2024-01-15T12:37:36.513394Z",
"url": "https://files.pythonhosted.org/packages/46/1a/c067cd7fa4db99b74e4b997def4abb3cc25a22f8e0e8bf68ce01fbc9be30/felimination-0.2.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-01-15 12:37:36",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ClaudioSalvatoreArcidiacono",
"github_project": "felimination",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "felimination"
}
