Toolbox for Multimodal Learn (scikit-Multimodallearn)

Dominique Benielli, Baptiste Bauvin, Sokol Koço, Riikka Huusari, Cécile Capponi, Hachem Kadri, François Laviolette

MLOSS 2022 pp. 1-7

/mloss/2022/benielli2022jmlr-toolbox/

Abstract

scikit-multimodallearn is a Python library for multimodal supervised learning, licensed under Free BSD, and compatible with the well-known scikit-learn toolbox (Fabian Pedregosa, 2011). This paper details the content of the library, including a specific multimodal data formatting and classification and regression algorithms. Use cases and examples are also provided.

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Cite

Text

Benielli et al. "Toolbox for Multimodal Learn (scikit-Multimodallearn)." Machine Learning Open Source Software, 2022.

Markdown

[Benielli et al. "Toolbox for Multimodal Learn (scikit-Multimodallearn)." Machine Learning Open Source Software, 2022.](https://mlanthology.org/mloss/2022/benielli2022jmlr-toolbox/)

BibTeX

@article{benielli2022jmlr-toolbox,
  title     = {{Toolbox for Multimodal Learn (scikit-Multimodallearn)}},
  author    = {Benielli, Dominique and Bauvin, Baptiste and Koço, Sokol and Huusari, Riikka and Capponi, Cécile and Kadri, Hachem and Laviolette, François},
  journal   = {Machine Learning Open Source Software},
  year      = {2022},
  pages     = {1-7},
  volume    = {23},
  url       = {https://mlanthology.org/mloss/2022/benielli2022jmlr-toolbox/}
}