Credal Transfer Learning With Multi-Estimation for Missing Data

Credal Transfer Learning With Multi-Estimation for Missing Data

Transfer learning (TL) has grown popular in recent years. It is effective to improve the classification accuracy in the target domain by using the training knowledge in the related domain (called source domain). However, the classification of missing data (or incomplete data) is a challenging task f...

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Bibliographic Details
Main Authors: Zongfang Ma, Zhe Liu, Yiru Zhang, Lin Song, Jihuan He
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Transfer learning
missing data
belief function
Credal classification
uncertainty
Online Access:https://ieeexplore.ieee.org/document/9046814/

Internet

https://ieeexplore.ieee.org/document/9046814/

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