Scikit-Learn compatible metrics with credible regions and confidence intervals

This library contains implementations of some scikit-learn metrics with credible regions and confidence intervals.

For installation and usage instructions, check-out our documentation.

Release files for credible 1.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for credible 1.1.1
File	Size	Uploaded
credible-1.1.1.tar.gz	66.8 kB	Jul 8, 2026	Details

Table of built distributions (wheels) for credible 1.1.1
File	Interpreter	ABI	Platform	Reset
credible-1.1.1-py3-none-any.whl 38.0 kB Jul 8, 2026	Python 3	none	any	Details

Total release size: 104.8 kB

Download URL	credible-1.1.1.tar.gz
Size	66.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`8649927e01620197725f72a5ea69fc76b0ccae9a23e79ad09d4ea46f216fcd69`
BLAKE2b-256 checksum How to use checksums	`b498f1f7139460a517d25c408c495617c3f3ef15d3a3d796043a18a529e121bb`
Upload date	Jul 8, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.13.9`

Download URL	credible-1.1.1-py3-none-any.whl
Size	38.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`677b6fb743b06cf9eb6e992d7509e3791f291781850a65345de8735e59f5800a`
BLAKE2b-256 checksum How to use checksums	`68bb0fde6fcdfa63ded4cb94990cf02cabf5f604ae45a4f2808152b436543653`
Upload date	Jul 8, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.13.9`