Leveraging Unseen Features along with their PLM-based Representation to Handle Negative Covariate Shift Problem in Text Classification
This paper presents a novel approach to address the problem of negative covariate shift by using unseen features. Covariate shift occurs when there is a drift between the data observed during the training and testing phase of a machine learning model. Covariate shift typically transpires in the nega...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-12-01
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| Series: | Foundations of Computing and Decision Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/fcds-2024-0020 |
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