The fuzzy support vector data description based on tightness for noisy label detection

Machine learning (ML) is an approach driven by data, and as research in machine learning progresses, the issue of noisy labels has garnered widespread attention. Noisy labels can significantly reduce the accuracy of supervised classification models, making it important to address this problem. There...

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Bibliographic Details
Published in:	Complex & intelligent systems Vol. 10; no. 3; pp. 4157 - 4174
Main Authors:	Wu, Xiaoying, Liu, Sanyang, Bai, Yiguang
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.06.2024 Springer Nature B.V Springer
Subjects:	Accuracy Algorithms Big Data Classification Complexity Computational Intelligence Data analysis Data Structures and Information Theory Datasets Density peak algorithm Engineering Image classification Labels Machine learning Membership function Noisy label detection Original Article Outliers (statistics) Random noise SVDD Tightness Density peak algorithm Membership function SVDD Noisy label detection Classification
ISSN:	2199-4536, 2198-6053
Online Access:	Get full text
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