Name
Abstract | ||
|---|---|---|
One major cause of performance degradation in predictive models is that the test samples are not well covered by the training data. Such not well-represented samples are called OoD samples. In this article, we propose OoDAnalyzer, a visual analysis approach for interactively identifying OoD samples and explaining them in context. Our approach integrates an ensemble OoD detection method and a grid-... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TVCG.2020.2973258 | IEEE Transactions on Visualization and Computer Graphics |
Keywords | DocType | Volume |
Training,Layout,Visualization,Dogs,Feature extraction,Approximation algorithms,Cats | Journal | 27 |
Issue | ISSN | Citations |
7 | 1077-2626 | 6 |
PageRank | References | Authors |
0.40 | 38 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changjian Chen | 1 | 17 | 2.19 |
| Jun Yuan | 2 | 244 | 23.10 |
| Yafeng Lu | 3 | 160 | 8.21 |
| Yang Liu | 4 | 1599 | 76.76 |
| Hang Su | 5 | 448 | 47.57 |
| Songtao Yuan | 6 | 7 | 1.45 |
| Shixia Liu | 7 | 2095 | 82.41 |