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MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning

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Author
Belmonte Pérez, Álvaro Andrés
Zafra Gómez, Amelia
Gibaja, Eva
Publisher
Elsevier
Date
2022
Subject
Multi-instance learning
Multi-label learning
Weka
Mulan
Classification
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Abstract
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.
URI
http://hdl.handle.net/10396/27493
Fuente
Belmonte, Á., Zafra, A., & Gibaja, E. (2022). MIML library: A modular and flexible library for multi-instance multi-label learning. Neurocomputing, 500, 632-636. https://doi.org/10.1016/j.neucom.2022.05.068
Versión del Editor
https://doi.org/10.1016/j.neucom.2022.05.068
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