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Cute Ranking

A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239.

PyPI - Python Version PyPI Status PyPI Status license

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:

  1. Mean Reciprocal Rank - mean_reciprocal_rank
  2. Relevancy Precision - r_precision
  3. Precision at K - precision_at_k
  4. Recall at K - recall_at_k
  5. F1 score at K - f1_score_at_k
  6. Average Precision - average_precision
  7. Mean Average Precision - mean_average_precision
  8. Discounted Cumulative Gain at K - dcg_at_k
  9. Normalized Discounted Cumulative Gain at K - ndcg_at_k
  10. Mean Rank - mean_rank
  11. 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 :).

About

A cute little python module for calculating different ranking metrics. Based entirely on the gist from @bwhite: https://gist.github.com/bwhite/3726239.

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