| Name | rank2plan JSON |
| Version |
0.2.0
JSON |
| download |
| home_page | None |
| Summary | None |
| upload_time | 2024-09-03 06:47:44 |
| maintainer | None |
| docs_url | None |
| author | Ryan Wang |
| requires_python | <4.0,>=3.9 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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# rank2plan
[](https://github.com/ryanxwang/rank2plan/actions/workflows/pytest.yml)
Implementation of constraint generation and column generation for solving large
L1-RankSVMs with hinge loss (with pair-specific gaps) and sample weights. This
is based on the work by Dedieu et al (2022) on solving large L1-SVMs with hinge
loss. See `documents/theory.pdf` for how we extend their work. The "2plan" part
of the package name comes from the tool being used to learn heuristics for
planning.
## Installation
Install with
```bash
pip install rank2plan
```
The PyPI release only supports `3.8 <= python <= 3.10` for now.
## Examples
See under `tests` for examples.
## Todo
- [ ] Support for sparse matrices and vectors
- [x] Bayesian optimisation for tuning the `C` value.
- [ ] We log pretty aggressively, probably should add a verbosity control
## References
- A. Dedieu, R. Mazumder, and H. Wang. Solving L1-regularized SVMs and Related
Linear Programs: Revisiting the Effectiveness of Column and Constraint
Generation. J. Mach. Learn. Res., 23:164:1–164:41, 2022. [[URL]](http://jmlr.org/papers/v23/19-104.html).
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