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
- Mean Rank -
mean_rank
- Hit@k -
hit_rate_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-0.0.2.tar.gz
(9.4 kB
view hashes)
Built Distribution
Close
Hashes for cute_ranking-0.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4065891762d626d85216a7fb2bc249ee91fc1d1070b4d3e7e8ab9d3f082cd12e |
|
MD5 | 08ea3e7b6f78bbe24e3fbde1b3e4185b |
|
BLAKE2b-256 | 2143c83fc0cebe3424508fc65164ac003517aa214928d2377b6ea32982678c97 |