JaccardDissimilarity[u,v]
gives the Jaccard dissimilarity between Boolean vectors u and v.


JaccardDissimilarity
JaccardDissimilarity[u,v]
gives the Jaccard dissimilarity between Boolean vectors u and v.
Details

- JaccardDissimilarity works for both True, False vectors and 0, 1 vectors.
- JaccardDissimilarity[u,v] is equivalent to (n10+n01)/(n11+n10+n01), where nij is the number of corresponding pairs of elements in u and v respectively equal to i and j.
Examples
open all close allBasic Examples (2)
Scope (2)
Applications (2)
Properties & Relations (5)
Jaccard dissimilarity is bounded by 0 and 1:
JaccardDissimilarity is greater than or equal to MatchingDissimilarity:
JaccardDissimilarity is greater than or equal to DiceDissimilarity:
JaccardDissimilarity is less than or equal to SokalSneathDissimilarity:
JaccardDissimilarity is less than or equal to RussellRaoDissimilarity:
Tech Notes
Related Guides
History
Text
Wolfram Research (2007), JaccardDissimilarity, Wolfram Language function, https://reference.wolfram.com/language/ref/JaccardDissimilarity.html.
CMS
Wolfram Language. 2007. "JaccardDissimilarity." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/JaccardDissimilarity.html.
APA
Wolfram Language. (2007). JaccardDissimilarity. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/JaccardDissimilarity.html
BibTeX
@misc{reference.wolfram_2025_jaccarddissimilarity, author="Wolfram Research", title="{JaccardDissimilarity}", year="2007", howpublished="\url{https://reference.wolfram.com/language/ref/JaccardDissimilarity.html}", note=[Accessed: 16-August-2025]}
BibLaTeX
@online{reference.wolfram_2025_jaccarddissimilarity, organization={Wolfram Research}, title={JaccardDissimilarity}, year={2007}, url={https://reference.wolfram.com/language/ref/JaccardDissimilarity.html}, note=[Accessed: 16-August-2025]}