Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918367715131392 |
|---|---|
| author | Trauger, Jacob Trauger, Tyson Tewari, Ambuj |
| author_facet | Trauger, Jacob Trauger, Tyson Tewari, Ambuj |
| contents | In this paper we will give a characterization of the learnability of forgiving 0-1 loss functions in the multiclass setting with effectively finite cardinality of the output and label space. To do this, we create a new combinatorial dimension that is based off of the Natarajan Dimension and we show that a hypothesis class is learnable in our setting if and only if this Generalized Natarajan Dimension is finite. We also show how this dimension characterizes other known learning settings such as a vast amount of instantiations of learning with set-valued feedback and a modified version of list learning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_08382 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions Trauger, Jacob Trauger, Tyson Tewari, Ambuj Machine Learning In this paper we will give a characterization of the learnability of forgiving 0-1 loss functions in the multiclass setting with effectively finite cardinality of the output and label space. To do this, we create a new combinatorial dimension that is based off of the Natarajan Dimension and we show that a hypothesis class is learnable in our setting if and only if this Generalized Natarajan Dimension is finite. We also show how this dimension characterizes other known learning settings such as a vast amount of instantiations of learning with set-valued feedback and a modified version of list learning. |
| title | Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2510.08382 |