OpenML-Python: an extensible Python API for OpenML

Matthias Feurer; Jan N. van Rijn; Arlind Kadra; Pieter Gijsbers; Neeratyoy Mallik; Sahithya Ravi; Andreas Müller; Joaquin Vanschoren; Frank Hutter

OpenML-Python: an extensible Python API for OpenML

Matthias Feurer, Jan N. van Rijn, Arlind Kadra, Pieter Gijsbers, Neeratyoy Mallik, Sahithya Ravi, Andreas Müller, Joaquin Vanschoren, Frank Hutter

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Abstract

OpenML is an online platform for open science collaboration in machine learning, used to share datasets and results of machine learning experiments. In this paper, we introduce OpenML-Python, a client API for Python, which opens up the OpenML platform for a wide range of Python-based machine learning tools. It provides easy access to all datasets, tasks and experiments on OpenML from within Python. It also provides functionality to conduct machine learning experiments, upload the results to OpenML, and reproduce results which are stored on OpenML. Furthermore, it comes with a scikit-learn extension and an extension mechanism to easily integrate other machine learning libraries written in Python into the OpenML ecosystem. Source code and documentation are available at https://github.com/openml/openml-python/.

Original language	English
Number of pages	5
Journal	Journal of Machine Learning Research
Volume	22
Publication status	Published - 2021

Bibliographical note

Funding Information:
MF, NM and FH acknowledge funding by the Robert Bosch GmbH. AK, JvR and FH acknowledge funding by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant no. 716721. JV and PG acknowledge funding by the Data Driven Discovery of Models (D3M) program run by DARPA and the Air Force Research Laboratory. The authors also thank Bilge Celik, Victor Gal and everyone listed at https://github.com/openml/openml-python/graphs/contributors for their contributions.

Publisher Copyright:
© 2021 Microtome Publishing. All rights reserved.

Funding

MF, NM and FH acknowledge funding by the Robert Bosch GmbH. AK, JvR and FH acknowledge funding by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant no. 716721. JV and PG acknowledge funding by the Data Driven Discovery of Models (D3M) program run by DARPA and the Air Force Research Laboratory. The authors also thank Bilge Celik, Victor Gal and everyone listed at https://github.com/openml/openml-python/graphs/contributors for their contributions.

Keywords

Collaborative Science
Meta-Learning
Python
Reproducible Research

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https://arxiv.org/abs/1911.02490

Cite this

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title = "OpenML-Python: an extensible Python API for OpenML",

abstract = "OpenML is an online platform for open science collaboration in machine learning, used to share datasets and results of machine learning experiments. In this paper, we introduce OpenML-Python, a client API for Python, which opens up the OpenML platform for a wide range of Python-based machine learning tools. It provides easy access to all datasets, tasks and experiments on OpenML from within Python. It also provides functionality to conduct machine learning experiments, upload the results to OpenML, and reproduce results which are stored on OpenML. Furthermore, it comes with a scikit-learn extension and an extension mechanism to easily integrate other machine learning libraries written in Python into the OpenML ecosystem. Source code and documentation are available at https://github.com/openml/openml-python/.",

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author = "Matthias Feurer and {van Rijn}, {Jan N.} and Arlind Kadra and Pieter Gijsbers and Neeratyoy Mallik and Sahithya Ravi and Andreas M{\"u}ller and Joaquin Vanschoren and Frank Hutter",

note = "Funding Information: MF, NM and FH acknowledge funding by the Robert Bosch GmbH. AK, JvR and FH acknowledge funding by the European Research Council (ERC) under the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant no. 716721. JV and PG acknowledge funding by the Data Driven Discovery of Models (D3M) program run by DARPA and the Air Force Research Laboratory. The authors also thank Bilge Celik, Victor Gal and everyone listed at https://github.com/openml/openml-python/graphs/contributors for their contributions. Publisher Copyright: {\textcopyright} 2021 Microtome Publishing. All rights reserved.",

year = "2021",

language = "English",

volume = "22",

journal = "Journal of Machine Learning Research",

issn = "1532-4435",

publisher = "Microtome Publishing",

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T2 - an extensible Python API for OpenML

AU - Feurer, Matthias

AU - van Rijn, Jan N.

AU - Kadra, Arlind

AU - Gijsbers, Pieter

AU - Mallik, Neeratyoy

AU - Ravi, Sahithya

AU - Müller, Andreas

AU - Vanschoren, Joaquin

AU - Hutter, Frank

N1 - Funding Information: MF, NM and FH acknowledge funding by the Robert Bosch GmbH. AK, JvR and FH acknowledge funding by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant no. 716721. JV and PG acknowledge funding by the Data Driven Discovery of Models (D3M) program run by DARPA and the Air Force Research Laboratory. The authors also thank Bilge Celik, Victor Gal and everyone listed at https://github.com/openml/openml-python/graphs/contributors for their contributions. Publisher Copyright: © 2021 Microtome Publishing. All rights reserved.

PY - 2021

Y1 - 2021

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AB - OpenML is an online platform for open science collaboration in machine learning, used to share datasets and results of machine learning experiments. In this paper, we introduce OpenML-Python, a client API for Python, which opens up the OpenML platform for a wide range of Python-based machine learning tools. It provides easy access to all datasets, tasks and experiments on OpenML from within Python. It also provides functionality to conduct machine learning experiments, upload the results to OpenML, and reproduce results which are stored on OpenML. Furthermore, it comes with a scikit-learn extension and an extension mechanism to easily integrate other machine learning libraries written in Python into the OpenML ecosystem. Source code and documentation are available at https://github.com/openml/openml-python/.

KW - Collaborative Science

KW - Meta-Learning

KW - Python

KW - Reproducible Research

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SN - 1532-4435

VL - 22

JO - Journal of Machine Learning Research

JF - Journal of Machine Learning Research

ER -

OpenML-Python: an extensible Python API for OpenML

Abstract

Bibliographical note

Funding

Keywords

Access to Document

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