False positive

A case that a check or matching step flagged wrongly: two different people treated as one, or a correct value reported as an error.

In matching, a false positive usually costs more than a miss, because merging two different people destroys information that is hard to get back.

Where it comes up

Near-duplicate recordsTwo rows describe the same real thing but differ enough that an exact comparison misses them.
Name variantsThe same person or organization appears under several spellings, orders, and abbreviations.

False negativeA real case that a check or matching step failed to flag: two records for the same customer left unmatched, or a wrong value that passed validation.
Match thresholdThe similarity score at or above which two records are treated as the same thing. Pairs scoring below it are left as separate records.
PrecisionFor numbers, how finely a value is recorded: 3.14159 carries more precision than 3.1. In matching and error detection the word has a second meaning: of everything that was flagged, how much was flagged correctly.

Karg checks for many of these when it profiles a file, applies the fixes it is confident about, and sets the rest aside for your review. See how it works, or have our team clean your data for you.