UFODMV: Unsupervised Feature Selection for Online Dynamic Multi-Views
In most machine learning (ML) applications, data that arrive from heterogeneous views (i.e., multiple heterogeneous sources of data) are more likely to provide complementary information than does a single view. Hence, these are known as <i>multi-view data</i>. In real-world applications,...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/7/4310 |