# How is levenshtein distance calculated?

**Levenshtein distance**is a measure of dissimilarity between two Strings. Mathematically, given two Strings x and y, the

**distance**measures the minimum number of character edits required to transform x into y. Typically three type of edits are allowed: Insertion of a character c.

Furthermore, how do you use levenshtein distance?

The **Levenshtein distance** is a number that tells you how different two strings are. The higher the number, the more different the two strings are. For example, the **Levenshtein distance** between “kitten” and “sitting” is 3 since, at a minimum, 3 edits are required to change one into the other.

**Hamming distance**. measures the minimum number of substitutions required to change one string into the other, or the minimum number. of errors that could have transformed one string into the other. The Lee

**distance**The

**Levenshtein distance**is a string. metric for measuring the difference between two sequences.

Similarly, how do you normalize levenshtein distance?

If you want the result to be in the range [0, 1] , you need to divide the **distance** by the maximum possible **distance** between two strings of given lengths. That is, length(str1)+length(str2) for the LCS **distance** and max(length(str1), length(str2)) for the **Levenshtein distance**.

**Minimum Edit distance** between two strings str1 and str2 is defined as the **minimum** number of insert/delete/substitute operations required to transform str1 into str2. You can also calculate **edit distance** as number of operations required to transform str2 into str1.