Add MRR (Mean Reciprocal Rank) metric to rec_sys#3572
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suportly wants to merge 1 commit intopytorch:masterfrom
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Add MRR (Mean Reciprocal Rank) metric to rec_sys#3572suportly wants to merge 1 commit intopytorch:masterfrom
suportly wants to merge 1 commit intopytorch:masterfrom
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Add Mean Reciprocal Rank metric for evaluating retrieval and recommendation systems. MRR measures the average of 1/rank of the first relevant item, supporting multiple top-k values and distributed computation, following the same pattern as HitRate. Refs pytorch#3569 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Duplicate of #3573 |
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Summary
MRR(Mean Reciprocal Rank) metric toignite/metrics/rec_sys/1/rankof the first relevant item across all queriesHitRate— supports multipletop_kvalues,ignore_zero_hits, distributed computation via@sync_all_reduceRefs #3569
New Files
ignite/metrics/rec_sys/mrr.py— MRR metric classtests/ignite/metrics/rec_sys/test_mrr_metric.py— 23 tests (all passing)Modified Files
ignite/metrics/rec_sys/__init__.py— export MRRignite/metrics/__init__.py— export MRR at top levelTest plan
from ignite.metrics import MRRworks correctly🤖 Generated with Claude Code