github_mirrors/vectorscan
3
0
Fork 1
mirror of https://github.com/VectorCamp/vectorscan.git synced 2025-06-28 16:41:01 +03:00
Code Issues Packages Projects Releases Wiki Activity

doc: make Wikipedia hyperlinks anonymous

Browse Source
This commit is contained in:
Justin Viiret 2017-11-07 14:43:58 +11:00 committed by Xiang Wang
parent ef7d920f79
commit d926e56a48
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
doc/dev-reference/compilation.rst
View File

@ -405,14 +405,14 @@ follows:
#. **Edit distance** is defined as Levenshtein distance. That is, there are #. **Edit distance** is defined as Levenshtein distance. That is, there are
three possible edit types considered: insertion, removal and substitution. three possible edit types considered: insertion, removal and substitution.
A more formal description can be found on A more formal description can be found on
`Wikipedia <https://en.wikipedia.org/wiki/Levenshtein_distance>`_. `Wikipedia <https://en.wikipedia.org/wiki/Levenshtein_distance>`__.
#. **Hamming distance** is the number of positions by which two strings of #. **Hamming distance** is the number of positions by which two strings of
equal length differ. That is, it is the number of substitutions required to equal length differ. That is, it is the number of substitutions required to
convert one string to the other. There are no insertions or removals when convert one string to the other. There are no insertions or removals when
approximate matching using a Hamming distance. A more formal description can approximate matching using a Hamming distance. A more formal description can
be found on be found on
`Wikipedia <https://en.wikipedia.org/wiki/Hamming_distance>`_. `Wikipedia <https://en.wikipedia.org/wiki/Hamming_distance>`__.
#. **Approximate matching** will match all *corpora* within a given edit or #. **Approximate matching** will match all *corpora* within a given edit or
Hamming distance. That is, given a pattern, approximate matching will match Hamming distance. That is, given a pattern, approximate matching will match