fuzzyJaccard

Calculates the fuzzy Jaccard index. The "normal" Jaccard index is given by <code>sum(A intersect B) / sum(A union B)</code>, where <code>A</code> and <code>B</code> are sets. Typically, <code>A</code> and <code>B</code> are binary outcomes, but the fuzzy version can accommodate values in [0, 1] and/or binary outcomes. The computationally efficient and equivalent method is <code>sum(pmin(A, B)) / (sum(A) + sum(B) - sum(pmin(A, B)))</code>. If <code>A</code> and <code>B</code> and both binary, the outcome is the same as the "plain" Jaccard index.

A collection of statistical and geometrical tools
including the aligned rank transform (ART; Higgins et al.
1990 <doi:10.4148/2475-7772.1443>; Peterson 2002
<doi:10.22237/jmasm/1020255240>; Wobbrock et al. 2011
<doi:10.1145/1978942.1978963>), 2-D histograms and
histograms with overlapping bins, a function for making all
possible formulae within a set of constraints, amongst others.

Adam B. Smith

statisfactory

Statistical and Geometrical Tools

fuzzyJaccard function

<dl><dt>a, b</dt>
<dd>Vectors of binary and/or values in the range [0, 1]. The vectors must be of the same length.</dd></dl>

Arguments

Fuzzy Jaccard index — fuzzyJaccard

<dl>

<dt>a, b</dt>
<dd>Vectors of binary and/or values in the range [0, 1]. The vectors must be of the same length.</dd>

</dl>

fuzzyJaccard: Fuzzy Jaccard index

Description

Usage

Value

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Examples