pytorch/ignite

Implementation of RecSys Metrics

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#2,631 opened on Jul 23, 2022

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 (12 comments) (0 reactions) (0 assignees)Python (4,313 stars) (602 forks)batch import
enhancementhelp wanted

Description

🚀 Feature

To add some more metrics used in Recommendation Systems with tests that can directly be used. Here is the list (@alykhantejani @vfdev-5 feel free to add more):

  • NDCG

Contributor guide

Tech stack
python
Domain
machine learning
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
familiarity with recommendation system metricsPyTorch basics
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
50
Research direction
Examine the existing NDCG implementation in the ignite/metrics/ directory to understand the pattern. Identify which metrics from the list are still missing (e.g., MAP, MRR, etc.). Implement each metric with unit tests following the existing test structure. Refer to common recommendation system metric definitions and ensure consistency with PyTorch tensor operations.