Metadata-Version: 2.1
Name: auto-sklearn
Version: 0.13.0
Summary: Automated machine learning.
Home-page: https://automl.github.io/auto-sklearn
Author: Matthias Feurer
Author-email: feurerm@informatik.uni-freiburg.de
License: BSD3
Description: # 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](http://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 a 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](http://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf) to publication.
        ```
        @inproceedings{feurer-neurips15a,
          title     = {Efficient and Robust Automated Machine Learning},
          author    = {Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum and Frank Hutter},
          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.
        ```
        @inproceedings{feurer-arxiv20a,
          title     = {Auto-Sklearn 2.0: The Next Generation},
          author    = {Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer and Frank Hutter},
          booktitle = {arXiv:2007.04074 [cs.LG]},
          year      = {2020}
        }
        ```
        
        ----------------------------------------
        
        Also, have a look at the blog on [automl.org](automl.org) where we regularly release blogposts.
Platform: Linux
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: examples
Provides-Extra: docs
