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29 April 2022 Research on loss function for adaptive label thresholding algorithm
Hongcheng Tang, Tingting Zhai
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Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 122471T (2022) https://doi.org/10.1117/12.2636819
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China
Abstract
The loss function plays a key role in the performance of online multi-label classification algorithms. Based on the design idea of the multi-label classification hinge loss function in the adaptive label thresholding algorithm, this paper expands several binary classification loss functions to new multi-label classification loss functions, proposes several adaptive label thresholding algorithms based on these new loss functions, and investigate the impact of different loss functions on multilabel classification performance. The experimental results show that the adaptive label thresholding algorithm based on the logistic loss function achieves the best performance, and the adaptive label thresholding algorithms using different loss functions are all better than several advanced comparison algorithms.
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Hongcheng Tang and Tingting Zhai "Research on loss function for adaptive label thresholding algorithm", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 122471T (29 April 2022); https://doi.org/10.1117/12.2636819
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KEYWORDS
Algorithm development
Data modeling
Machine learning
Optimization (mathematics)
Stochastic processes
Scene classification
Transform theory
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