Incorporating manifold regularization into adaptive label thresholding algorithm for online semi-supervised multi-label classification

Online multi-label classification aims to assign multiple appropriate categories to arriving instances. Currently, most approaches focus on supervised scenarios where instances are all labeled. The adaptive label thresholding approach, for example, can dynamically adjust the label threshold for labe...

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Bibliographic Details
Published in:Evolving systems Vol. 16; no. 4; p. 124
Main Authors: Fang, Nannan, Zhai, Tingting
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2025
Springer Nature B.V
Subjects:
Adaptive algorithms
Algorithms
Artificial Intelligence
Classification
Complex Systems
Complexity
Datasets
Distance learning
Engineering
Feature selection
Labels
Manifolds
Optimization
Original Paper
Regularization
Regularization methods
Online multi-label classification
Adaptive label thresholding
Online semi-supervised learning
Manifold regularization
ISSN:1868-6478, 1868-6486
Online Access:Get full text
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