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MUSE

Description: This package provides the demo implementation of MUSE (i.e. Multi-Label Selective Ensemble), which builds a selective ensemble based on a set of component multi-label classifiers. During the process of building selective ensemble, the concerned performance measure (such as hamming loss, F1-score, One-error, etc) can considered. A readme file is included in the package.

References: Nan Li, Yuang Jiang, Zhi-Hua Zhou. Multi-label selective ensemble. In: Proceedings of the 12th International Workshop on Multiple Classifier Systems (MCS¡¯15), G¨¹nzburg, Germany, 2015.

ATTN: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Prof. Zhi-Hua Zhou (zhouzh@nju.edu.cn).

Requirement: This package is developed with MATLAB.

ATTN2: This package was developed by Mr. Nan Li (lin@lamda.nju.edu.cn). The readme file and demo roughly explains how to use the codes. For any problem concerning the codes, please feel free to contact Mr. Li.

Download: [code] (6KB)
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