algo-rank-bayesian
Bayesian Average Rating
Overview
Bayesian average combines an item's observed average rating with a prior (global average), weighted by review count. Formula: BR = (C × m + Σrᵢ) / (C + n) where m=global mean, C=confidence parameter, n=item reviews, Σrᵢ=sum of item ratings. Items with few reviews are pulled toward the global mean.
When to Use
Trigger conditions:
- Ranking items by continuous ratings (1-5 stars) with varying review counts
- IMDB-style "Top 250" lists that balance quality and popularity
- Any rating aggregation where new items shouldn't dominate with few high ratings
When NOT to use:
- For binary (upvote/downvote) data (use Wilson Score instead)
- When all items have similar review counts (simple average is sufficient)
Algorithm
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