Rust implementation of Bayesian Additive Regression Trees for Probabilistic programming with PyMC
Project description
bart-rs
A high-performance Rust implementation of an optimized Particle Gibbs BART (PGBART) sampler. This is the sampler used by pymc-bart.
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bart-rs is available on PyPI with a pre-built wheels for Linux, MacOS and Windows.
pip install bartrs
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|
|
| BLAKE2b-256 |
99d335d5700f203fcd55557157df160002884d0b89b698cc29941ae7bfd4b978
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Provenance
The following attestation bundles were made for bartrs-0.3.0-cp312-cp312-macosx_10_12_x86_64.whl:
Publisher:
pypi.yml on pymc-devs/bartrs
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
bartrs-0.3.0-cp312-cp312-macosx_10_12_x86_64.whl -
Subject digest:
df79127c464abc8f5ac7751f39a9639c98563785919cb73d2fca5776a17f220f - Sigstore transparency entry: 1764377337
- Sigstore integration time:
-
Permalink:
pymc-devs/bartrs@f9267cf63a61c56355dc0f5216a2748b11083c0f -
Branch / Tag:
refs/tags/v0.3.0 - Owner: https://github.com/pymc-devs
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
pypi.yml@f9267cf63a61c56355dc0f5216a2748b11083c0f -
Trigger Event:
release
-
Statement type: