Visual exploration of multi-dimensional data via rule-based sample embedding
We propose an approach to learning sample embedding for analyzing multi-dimensional datasets. The basic idea is to extract rules from the given dataset and learn the embedding for each sample based on the rules it satisfies. The approach can filter out pattern-irrelevant attributes, leading to signi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-09-01
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| Series: | Visual Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468502X24000469 |
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