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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.08056 |
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| _version_ | 1866909105042489344 |
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| author | Belmonte, Álvaro Zafra, Amelia Gibaja, Eva |
| author_facet | Belmonte, Álvaro Zafra, Amelia Gibaja, Eva |
| contents | MIML library is a Java software tool to develop, test, and compare classification algorithms for multi-instance multi-label (MIML) learning. The library includes 43 algorithms and provides a specific format and facilities for data managing and partitioning, holdout and cross-validation methods, standard metrics for performance evaluation, and generation of reports. In addition, algorithms can be executed through $xml$ configuration files without needing to program. It is platform-independent, extensible, free, open-source, and available on GitHub under the GNU General Public License. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_08056 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning Belmonte, Álvaro Zafra, Amelia Gibaja, Eva Machine Learning MIML library is a Java software tool to develop, test, and compare classification algorithms for multi-instance multi-label (MIML) learning. The library includes 43 algorithms and provides a specific format and facilities for data managing and partitioning, holdout and cross-validation methods, standard metrics for performance evaluation, and generation of reports. In addition, algorithms can be executed through $xml$ configuration files without needing to program. It is platform-independent, extensible, free, open-source, and available on GitHub under the GNU General Public License. |
| title | MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2402.08056 |