Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertai...

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Bibliographic Details
Main Authors: Ying Lv, Bofeng Zhang, Guobing Zou, Xiaodong Yue, Zhikang Xu, Haiyan Li
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Entropy
Subjects:
domain adaptation
transfer learning
evidence theory
uncertainty measure
Online Access:https://www.mdpi.com/1099-4300/24/7/966

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https://www.mdpi.com/1099-4300/24/7/966

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