Jaccard index: Difference between revisions
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The '''Jaccard index''', also known as the '''Jaccard similarity coefficient''', is a statistic used for gauging the similarity and diversity of sample sets. It was developed by Paul Jaccard, originally giving the French name ''coefficient de communauté'', and independently formulated again by T. Tanimoto. Thus, the '''Tanimoto index''' or '''Tanimoto coefficient''' are also used in some fields. However, they are identical in generally taking the ratio of '''Intersection over Union'''. The Jaccard coefficient measures similarity between finite sample sets, and is defined as the size of the intersection divided by the size of the union of the sample sets:
:J(A, B) = |A ∩ B|/|A ∪ B|
<br><br>
=={{header|Wren}}==
{{libheader|Wren-set}}
Note that the Set object in the above module is implemented as a Map and consequently the iteration order (and the order in which elements are printed) is undefined.
<lang ecmascript>import "./set" for Set
var jacardIndex = Fn.new { |a, b|
if (a.count == 0 && b.count == 0) return 1
return a.intersect(b).count / a.union(b).count
}
var a = Set.new([1, 2, 3, 4, 5, 6])
var b = Set.new([3, 4, 5, 6, 7, 8])
System.print("a = %(a)")
System.print("b = %(b)")
System.print("J(a, b) = %(jacardIndex.call(a, b))")</lang>
{{out}}
<pre>
a = <2, 1, 3, 5, 4, 6>
b = <3, 5, 8, 7, 4, 6>
J(a, b) = 0.5
</pre>
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