Metric retrieval recall at precision

[MrShevan]

What does this PR do?

Hello, @stancld ! It's a draft PR for issue: Fixes #780

I still think about how to add more tests, testing pattern in this repo is pretty hard, but the general idea of RetrievalRecallAtFixedPrecision is implemented.

Keep working 🛠

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• Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
• Did you read the contributor guideline, Pull Request section?
• Did you make sure to update the docs?
• Did you write any new necessary tests?

PR review

Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.

Did you have fun?

Make sure you had fun coding 🙃

[Borda]

@MrShevan, how is it going here? 🐰

[MrShevan]

Hi! Sorry was busy at the end of the week, I keep working on PR. I'm still thinking about my implementation. Was it right to inherit from Metric class instead RetrievalMetric? I decided to do so to compute recall and precision metrics for all k and return two values: best recall and the value in which it is achieved.

[codecov]

Codecov Report

Merging #951 (f9dd87f) into master (f8ff34e) will decrease coverage by 0%.
The diff coverage is 86%.

@@          Coverage Diff           @@
##           master   #951    +/-   ##
======================================
- Coverage      95%    95%    -0%     
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  Files         177    179     +2     
  Lines        7522   7631   +109     
======================================
+ Hits         7148   7229    +81     
- Misses        374    402    +28     

[MrShevan]

@stancld @Borda @SkafteNicki
Thanks for your comments :) I tried to take into account all your comments:

1. Firstly I I concentrated on the precision-recall curve as noticed @stancld instead of the varying k and made it main logic as functional, which used in module, thanks @Borda for advise.
2. I resolved all comments from @SkafteNicki.
3. I spent a little more time for such tests, but now they are all passed, when running locally. :)

[SkafteNicki]

LGTM

[MrShevan]

@Borda @stancld @SkafteNicki
I enjoyed working on this issue, thanks a lot for your involvement :]

[Borda]

I enjoyed working on this issue, thanks a lot for your involvement :]

great contribution!

[stancld]

@MrShevan Thanks a lot for your great contribution! :)