Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.09965 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917590867116032 |
|---|---|
| author | Yegang, Han Minjun, Park Duwon, Byun Inkyu, Park |
| author_facet | Yegang, Han Minjun, Park Duwon, Byun Inkyu, Park |
| contents | When there are models with clear-cut judgment results for several data points, it is possible that most models exhibit a relationship where if they correctly judge one target, they also correctly judge another target. Conversely, if most models incorrectly judge one target, they may also incorrectly judge another target. We propose a method for visualizing this hierarchy among targets. This information is expected to be beneficial for model improvement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_09965 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Hierarchy Representation of Data in Machine Learnings Yegang, Han Minjun, Park Duwon, Byun Inkyu, Park Machine Learning Artificial Intelligence When there are models with clear-cut judgment results for several data points, it is possible that most models exhibit a relationship where if they correctly judge one target, they also correctly judge another target. Conversely, if most models incorrectly judge one target, they may also incorrectly judge another target. We propose a method for visualizing this hierarchy among targets. This information is expected to be beneficial for model improvement. |
| title | Hierarchy Representation of Data in Machine Learnings |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2402.09965 |