Skip to main content

Minimal package to evaluate machine learning models with scikit-learn

Project description

scikit-eval

🚧 Work in progress

scikit-eval aims to offer a lightweight and simple Experiment class to evaluate your machine learning models.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scikit-eval-0.1.0.tar.gz (1.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

scikit_eval-0.1.0-py3-none-any.whl (1.4 kB view details)

Uploaded Python 3

File details

Details for the file scikit-eval-0.1.0.tar.gz.

File metadata

  • Download URL: scikit-eval-0.1.0.tar.gz
  • Upload date:
  • Size: 1.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: pdm/2.8.0 CPython/3.11.4

File hashes

Hashes for scikit-eval-0.1.0.tar.gz
Algorithm Hash digest
SHA256 7dc370ce17b3f5c964cd9961061f817bb79a6cad536eac558a84d0b2eaade196
MD5 36ed1cf778af8ccf989319ff2eab24fa
BLAKE2b-256 d23d64531fcd2954eba47361d96dc058447640de59a888f018389c625285bc30

See more details on using hashes here.

File details

Details for the file scikit_eval-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: scikit_eval-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 1.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: pdm/2.8.0 CPython/3.11.4

File hashes

Hashes for scikit_eval-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e502f5c026adeb30d182cdacfc032c57847200e66c3e570f58c86b7f59b0f935
MD5 81111f2509c6ba4c2be3d3d0722a61c1
BLAKE2b-256 d97ced82a8ebe3438207280dd4599540d9cb415bfbc4e739e04c6e94cf8dbbd9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page