LevenshteinDistance Function | Teradata Vantage - LevenshteinDistance (ML Engine) - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
9.02
9.01
2.0
1.3
Published
February 2022
Language
English (United States)
Last Update
2022-02-10
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rnn1580259159235.ditamap
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dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

The LevenshteinDistance function computes the Levenshtein distance between two text values. The Levenshtein distance (or edit distance) is the number of edits needed to transform one string into the other. An edit is an insertion, deletion, or substitution of a single character.

The Levenshtein distance is useful for fuzzy matching of sequences and strings. The LevenshteinDistance function is often used to resolve a user-entered value to a standard value. For example, when a enters "Jon Dow" when searching for "John Doe".

A typical application of the LevenshteinDistance function is genome sequencing.