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https://github.com/edublancas/sklearn-evaluation
Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
https://github.com/edublancas/sklearn-evaluation
Last synced: 4 months ago
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Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
- Host: GitHub
- URL: https://github.com/edublancas/sklearn-evaluation
- Owner: edublancas
- License: mit
- Fork: true (ploomber/sklearn-evaluation)
- Created: 2023-01-15T21:18:52.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2023-01-15T22:50:39.000Z (about 2 years ago)
- Last Synced: 2024-08-01T18:28:27.096Z (7 months ago)
- Homepage: https://sklearn-evaluation.ploomber.io
- Size: 12.9 MB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- awesome-datascience - sklearn-evaluation
README
# sklearn-evaluation

[](https://sklearn-evaluation.readthedocs.io/en/latest/?badge=latest)
[](https://badge.fury.io/py/sklearn-evaluation)
[](https://coveralls.io/github/ploomber/sklearn-evaluation)
[](https://twitter.com/intent/user?screen_name=ploomber)
[](https://github.com/psf/black)
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YouTubeMachine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking, and Jupyter notebook analysis.
Supports Python 3.7 and higher. Tested on Linux, macOS and Windows.
*Note:* Recent versions likely work on Python 3.6, however, `0.8.2` was the latest version we tested with Python 3.6.

# Install
```bash
pip install sklearn-evaluation
```# Features
* [Plotting](https://sklearn-evaluation.ploomber.io/en/latest/classification/basic.html) (confusion matrix, feature importances, precision-recall, roc, elbow curve, silhouette plot)
* Report generation ([example](https://htmlpreview.github.io/?https://github.com/ploomber/sklearn-evaluation/blob/master/examples/report.html))
* [Evaluate grid search results](https://sklearn-evaluation.ploomber.io/en/latest/optimization/grid_search.html)
* [Track experiments using a local SQLite database](https://sklearn-evaluation.ploomber.io/en/latest/comparison/SQLiteTracker.html)
* [Analyze notebooks output](https://sklearn-evaluation.ploomber.io/en/latest/comparison/NotebookCollection.html)
* [Query notebooks with SQL](https://sklearn-evaluation.ploomber.io/en/latest/comparison/nbdb.html)