← Glossary
Matching
also called pair classification
Matching is the stage of entity matching that decides, for each candidate pair produced by blocking, whether the two records refer to the same real-world entity.
Matching runs only on the candidate pairs that survived blocking, so it can afford to be precise. It classifies each pair as a match or not, using anything from hand-authored rules to supervised machine learning.
The key metric for matching is precision, alongside recall: of the pairs it labels a match, how many truly are? A learned matcher reaches high accuracy on hard, varied domains, at the cost of needing labeled examples. MadMatcher’s MatchFlow trains a classifier such as XGBoost or Random Forest on your labels.