Overview
Precision-recall-gain curves for Python
Free software: MIT license
Installation
pip install precision-recall-gain
You can also install the in-development version with:
pip install https://github.com/crypdick/precision-recall-gain/archive/master.zip
Documentation
Development
To run all the tests run:
tox
Note, to combine the coverage data from all the tox environments run:
Windows |
set PYTEST_ADDOPTS=--cov-append tox |
|---|---|
Other |
PYTEST_ADDOPTS=--cov-append tox |
References
[Precision-Recall-Gain Curves: PR Analysis Done Right (2015) by Peter A. Flach and Meelis Kull](https://papers.nips.cc/paper/2015/file/33e8075e9970de0cfea955afd4644bb2-Paper.pdf)
[sklearn-compatible implementation](https://github.com/scikit-learn/scikit-learn/pull/24121) by [Bradley Fowler](https://github.com/bradleyfowler123)
[PRG curves](https://www.biostat.wisc.edu/~page/rocprg.pdf) by [David Page](https://www.biostat.wisc.edu/~page/)
[Blog post by Bradley Fowler](https://snorkel.ai/improving-upon-precision-recall-and-f1-with-gain-metrics/)
[Original implementation](https://github.com/meeliskull/prg) by [Meelis Kull](https://github.com/meeliskull)
Changelog
0.0.0 (2021-03-20)
First release on PyPI.
1 maintainer
Metadata
1 maintainer
Release files for precision-recall-gain 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| precision-recall-gain-0.1.1.tar.gz | 29.2 kB | Without provenance | Details |
Release files / precision-recall-gain-0.1.1.tar.gz
| Download URL | precision-recall-gain-0.1.1.tar.gz |
|---|---|
| Size | 29.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3431e02edcbe7b2254b53ab4447e42e409dea8060efaf259e8378eb9e23816d1
|
|
BLAKE2b-256 checksum How to use checksums |
e717f06820fcafe93299d1277ce6ff52139b54056cf2f8932b7c5613a5fbbdaf
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.11.7
|
Security for precision-recall-gain 0.1.1
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.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
