Available metrics:
cosine(a, b): Cosine similarity between sets/vectors.expl1(a, b): Exponentiated L1 distance between vectors.expl2(a, b): Exponentiated L2 distance between vectors.jaccard(a, b): Cardinality of intersection divided by cardinality of union for Set's and IntSet's, extended Jaccard definition for AbstractVector's.matching(a, b): Cardinality of intersection for Set's and IntSet's, dot product for AbstractVector's. Sometimes called the Simple Matching Coefficient.overlap(a, b): Cardinality of intersection divided by minimum of cardinality of two inputs. AbstractVector's use definition like extended Jaccard.pearson(a, b): Pearson correlation between sets/vectors.
Measuring the similarity between sets:
using SimilarityMetrics
a, b = Set{ASCIIString}(), Set{ASCIIString}()
add!(a, "a")
add!(a, "b")
add!(b, "b")
add!(b, "c")
cosine(a, b)
expl1(a, b)
expl2(a, b)
jaccard(a, b)
matching(a, b)
overlap(a, b)
pearson(a, b)
Measuring the similarity between vectors:
a, b = [0, 0, 0, 0], [0, 0, 0, 0]
a[1] = 1
a[2] = 1
b[2] = 1
b[3] = 1
cosine(a, b)
expl1(a, b)
expl2(a, b)
jaccard(a, b)
matching(a, b)
overlap(a, b)
pearson(a, b)