A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239.
Project description
Cute Ranking
A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239.
Install
Requires a minimum python installation of 3.6
pip install cute_ranking
How to use
from cute_ranking.core import mean_reciprocal_rank
relevancies = [[0, 0, 1], [0, 1, 0], [1, 0, 0]]
mean_reciprocal_rank(relevancies)
0.611111111111111
The library current supports the following information retrieval ranking metrics:
- Mean Reciprocal Rank -
mean_reciprocal_rank
- Relevancy Precision -
r_precision
- Precision at K -
precision_at_k
- Average Precision -
average_precision
- Mean Average Precision -
mean_average_precision
- Discounted Cumulative Gain at K -
dcg_at_k
- Normalized Discounted Cumulative Gain at K -
ndcg_at_k
Contributing
PRs and issues welcome! Please make sure to read through the CONTRIBUTING.md
doc for how to contribute :).
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
cute_ranking-0.0.1.tar.gz
(9.0 kB
view hashes)
Built Distribution
Close
Hashes for cute_ranking-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c975f9d8877e4c5c32379cf90bdf38460b0dc6eb68547197ace5ae6f6b02af2e |
|
MD5 | eb8e14fac3db280345eabe2cdd78d979 |
|
BLAKE2b-256 | 17b086aa3dd5771758d9b0296fbdf4b09b8389628719b331ce9a5c5d04ae7778 |