Takes two sets of ratings, e.g. for two items from an online store, and computes an estimate for the probability that the first item is truly more highly rated on average than the second.

Compare ratings, e.g. for two items from an online store, and compute an estimate for the probability that the first item is truly more highly rated on average than the second. The computation uses a state of the art empirical bayesian model requiring no specification of any prior distribution, which has been trained on a large database of Amazon reviews.

Currently RaterBayes accepts data in the 1-star to 5-star rating format and assumes that the number of stars given by each person are known, but additional features are planned for working with other types of data.

A new endpoint allows the URLs for two Amazon products for comparison to be specified directly