https://github.com/automl/auto-sklearn

Automated Machine Learning with scikit-learn
https://github.com/automl/auto-sklearn

automated-machine-learning automl bayesian-optimization hyperparameter-optimization hyperparameter-search hyperparameter-tuning meta-learning metalearning scikit-learn smac

Last synced: 10 days ago
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Automated Machine Learning with scikit-learn

• Host: GitHub
• URL: https://github.com/automl/auto-sklearn
• Owner: automl
• License: bsd-3-clause
• Created: 2015-07-02T15:38:10.000Z (over 9 years ago)
• Default Branch: development
• Last Pushed: 2023-12-25T14:05:19.000Z (11 months ago)
• Last Synced: 2024-04-14T15:24:37.836Z (7 months ago)
• Topics: automated-machine-learning, automl, bayesian-optimization, hyperparameter-optimization, hyperparameter-search, hyperparameter-tuning, meta-learning, metalearning, scikit-learn, smac
• Language: Python
• Homepage: https://automl.github.io/auto-sklearn
• Size: 121 MB
• Stars: 7,392
• Watchers: 215
• Forks: 1,264
• Open Issues: 193
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.txt
  • Citation: CITATION.cff

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README

        
# auto-sklearn

**auto-sklearn** is an automated machine learning toolkit and a drop-in replacement for a [scikit-learn](https://scikit-learn.org) estimator.

Find the documentation **[here](https://automl.github.io/auto-sklearn/)**. Quick links:

  * [Installation Guide](https://automl.github.io/auto-sklearn/master/installation.html)

  * [Releases](https://automl.github.io/auto-sklearn/master/releases.html)

  * [Manual](https://automl.github.io/auto-sklearn/master/manual.html)

  * [Examples](https://automl.github.io/auto-sklearn/master/examples/index.html)

  * [API](https://automl.github.io/auto-sklearn/master/api.html)

## auto-sklearn in one image

![image](doc/images/askl_pipeline.png)

## auto-sklearn in four lines of code

```python

import autosklearn.classification

cls = autosklearn.classification.AutoSklearnClassifier()

cls.fit(X_train, y_train)

predictions = cls.predict(X_test)

```

## Relevant publications

If you use auto-sklearn in scientific publications, we would appreciate citations.

**Efficient and Robust Automated Machine Learning**

*Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum and Frank Hutter*

Advances in Neural Information Processing Systems 28 (2015)

[Link](https://papers.neurips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf) to publication.

```

@inproceedings{feurer-neurips15a,

    title     = {Efficient and Robust Automated Machine Learning},

    author    = {Feurer, Matthias and Klein, Aaron and Eggensperger, Katharina and Springenberg, Jost and Blum, Manuel and Hutter, Frank},

    booktitle = {Advances in Neural Information Processing Systems 28 (2015)},

    pages     = {2962--2970},

    year      = {2015}

}

```

----------------------------------------

**Auto-Sklearn 2.0: The Next Generation**

*Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer and Frank Hutter**

arXiv:2007.04074 [cs.LG], 2020

[Link](https://arxiv.org/abs/2007.04074) to publication.

```

@article{feurer-arxiv20a,

    title     = {Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning},

    author    = {Feurer, Matthias and Eggensperger, Katharina and Falkner, Stefan and Lindauer, Marius and Hutter, Frank},

    booktitle = {arXiv:2007.04074 [cs.LG]},

    year      = {2020}

}

```

----------------------------------------

Also, have a look at the blog on [automl.org](https://automl.org) where we regularly release blogposts.