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False flag: An evolutionary false labeling approach for multilabel classification

delete2026-02-27
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OA
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N
Nicolás García‐Pedrajas *
J
José M. Cuevas-Muñoz
M
Manuel Mendoza-Hurtado
J
Javier Pérez-Rodríguez
A
Aida de Haro-García
DOI：10.1016/j.asoc.2026.114912delete
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Abstract

Abstract

En 中文
• We present a new method for improving multi-label classification. • The method relies on modifying the training set’s labels to enhance results. • The comparison utilizes four different metrics. • We study the method’s performance in the context of missing labels.
Keywords:
Multilabel problems
False labels
Missing labels
Evolutionary computation
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

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No organization information available