ml_edm package: a Python toolkit for Machine Learning based Early Decision Making
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910574820982784 |
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| author | Renault, Aurélien Achenchabe, Youssef Bertrand, Édouard Bondu, Alexis Cornuéjols, Antoine Lemaire, Vincent Dachraoui, Asma |
| author_facet | Renault, Aurélien Achenchabe, Youssef Bertrand, Édouard Bondu, Alexis Cornuéjols, Antoine Lemaire, Vincent Dachraoui, Asma |
| contents | \texttt{ml\_edm} is a Python 3 library, designed for early decision making of any learning tasks involving temporal/sequential data. The package is also modular, providing researchers an easy way to implement their own triggering strategy for classification, regression or any machine learning task. As of now, many Early Classification of Time Series (ECTS) state-of-the-art algorithms, are efficiently implemented in the library leveraging parallel computation. The syntax follows the one introduce in \texttt{scikit-learn}, making estimators and pipelines compatible with \texttt{ml\_edm}. This software is distributed over the BSD-3-Clause license, source code can be found at \url{https://github.com/ML-EDM/ml_edm}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_12925 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ml_edm package: a Python toolkit for Machine Learning based Early Decision Making Renault, Aurélien Achenchabe, Youssef Bertrand, Édouard Bondu, Alexis Cornuéjols, Antoine Lemaire, Vincent Dachraoui, Asma Machine Learning \texttt{ml\_edm} is a Python 3 library, designed for early decision making of any learning tasks involving temporal/sequential data. The package is also modular, providing researchers an easy way to implement their own triggering strategy for classification, regression or any machine learning task. As of now, many Early Classification of Time Series (ECTS) state-of-the-art algorithms, are efficiently implemented in the library leveraging parallel computation. The syntax follows the one introduce in \texttt{scikit-learn}, making estimators and pipelines compatible with \texttt{ml\_edm}. This software is distributed over the BSD-3-Clause license, source code can be found at \url{https://github.com/ML-EDM/ml_edm}. |
| title | ml_edm package: a Python toolkit for Machine Learning based Early Decision Making |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2408.12925 |