Edit distance is a measure of how different two strings are based on the minimum number or cost of operations needed to transform one string into the other. It is used in spell correction, fuzzy matching, search, natural language processing, and approximate string comparison.
A measurement of how similar two text strings are to each other. In machine learning, edit distance is useful for the following reasons: - Edit distance is easy to compute. - Edit distance can compare two strings known to be similar to each other. - Edit distance can determine the degree to which different strings are similar to a given string. Several definitions of edit distance exist, each using different string operations. See Levenshtein distance for an example.