The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization
Abstract
In multilabel learning, each instance in the training set is associated with a set of labels and the task is to output a label set whose size is unknown a priori for each unseen instance. In this paper, this problem is addressed in the way that a neural network algorithm named BP-MLL, i.e., Backpropagation for Multilabel Learning, is proposed. It is derived from the popular Backpropogation algorithm through employing a novel error function capturing the characteristics of multilabel learning, i.e., the labels belonging to an instance should be ranked higher than those not belonging to that instance. Applications to two real-world multilabel learning problems, i.e., functional genomics and text categorization, show that the performance of BP-MLL is superior to that of some well-established multilabel learning algorithms.
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Cited by
Deep Learning for Extreme Multi-label Text Classification
Liu, J., Chang, W.-C., Wu, Y., & Yang, Y. (2017) · Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3077136.3080834 · Cited by 676
Emotion classification for short texts: an improved multi-label method
Liu, X., Shi, T., Zhou, G., Liu, M., Yin, Z., Yin, L., & Zheng, W. (2023) · Humanities and Social Sciences Communications · doi:10.1057/s41599-023-01816-6 · Cited by 175
Presence-Only Geographical Priors for Fine-Grained Image Classification
Aodha, O. M., Cole, E., & Perona, P. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00969 · Cited by 149
Co-design of human-centered, explainable AI for clinical decision support
Panigutti, C., Beretta, A., Fadda, D., Giannotti, F., Pedreschi, D., Perotti, A., & Rinzivillo, S. (2023) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3587271 · Cited by 127
Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction
Cauchois, M., Gupta, S., & Duchi, J. (2020) · arXiv · doi:10.48550/arxiv.2004.10181 · Cited by 31
Metadata
- Authors
- Zhang, M.-L., & Zhou, Z.-H.
- Venue
- IEEE Transactions on Knowledge and Data Engineering
- Published
- 2006-10
- Volume
- 18
- Issue
- 10
- Pages
- 1338-1351
- ISSN
- 1041-4347 (ISSN-L)
- OpenAlex
- W2119466907
- Cited by
- 1,187
- References
- 5
- FWCI
- 16.46
- Type
- journal article
- Language
- en
- Open access
- closed
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