MLJ: A Julia package for composable machine learning

Jupyter Notebook Julia Submitted 21 July 2020Published 07 November 2020
Review

Editor: @terrytangyuan (all papers)
Reviewers: @degleris1 (all reviews), @henrykironde (all reviews)

Authors

Anthony D. Blaom (0000-0001-6689-886X), Franz Kiraly (0000-0002-9254-793X), Thibaut Lienart, Yiannis Simillides (0000-0002-0287-8699), Diego Arenas (0000-0001-7829-6102), Sebastian J. Vollmer (0000-0002-9025-0753)

Citation

Blaom et al., (2020). MLJ: A Julia package for composable machine learning. Journal of Open Source Software, 5(55), 2704, https://doi.org/10.21105/joss.02704

@article{Blaom2020, doi = {10.21105/joss.02704}, url = {https://doi.org/10.21105/joss.02704}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {55}, pages = {2704}, author = {Anthony D. Blaom and Franz Kiraly and Thibaut Lienart and Yiannis Simillides and Diego Arenas and Sebastian J. Vollmer}, title = {MLJ: A Julia package for composable machine learning}, journal = {Journal of Open Source Software} }
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Machine Learning model composition stacking ensembling hyper-parameter tuning

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ISSN 2475-9066