Leveraging Expert Knowledge for Label Noise Mitigation in Machine Learning

In training-based Machine Learning applications, the training data are frequently labeled by non-experts and expose substantial label noise which greatly alters the training models. In this work, a novel method for reducing the effect of label noise is introduced. The rules are created from expert k...

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Autores principales: Quoc Nguyen, Tomoaki Shikina, Daichi Teruya, Seiji Hotta, Huy-Dung Han, Hironori Nakajo
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/10b06feac2404b61b1fc2aab9d800a26
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