Anchor Boosting
Efficient tree-based nonlinear anchor regression and classification for Python.
If you use this, please consider citing
article{londschien2025,
title={Domain Generalization and Adaptation in Intensive Care with Anchor Regression},
author={Londschien, Malte, Burger, Manuel, R{\"a}tsch, Gunnar and B{\"u}hlmann, Peter},
journal={arXiv preprint arXiv:2507.21783},
year={2025}
}
1 maintainer
Release files for anchorboosting 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| anchorboosting-0.3.0.tar.gz | 20.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| anchorboosting-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.1 kB
Release files / anchorboosting-0.3.0.tar.gz
| Download URL | anchorboosting-0.3.0.tar.gz |
|---|---|
| Size | 20.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
797439b17b820177926c5cbf77a2a881a6967b3a57baac3fd5148867ada4ee5d
|
|
BLAKE2b-256 checksum How to use checksums |
f431b21521b9fc5cb474e41651aa8a91542d700587a03b0eb5ac54b12fe32f61
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 15, 2025.
Transparency logRelease files / anchorboosting-0.3.0-py3-none-any.whl
| Download URL | anchorboosting-0.3.0-py3-none-any.whl |
|---|---|
| Size | 10.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e4646db0fe8d53906551e7f75d489d5dc5f9a50c6fc84a2551a31789b70f550c
|
|
BLAKE2b-256 checksum How to use checksums |
a4289ecb5e522ee54e92bf9fab10c909297bc308692bc267669ca46036721637
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 15, 2025.
Transparency log
