comparator implements comparison functions for clustering and record linkage applications. It includes functions for comparing strings, sequences and numeric vectors. Where possible, comparators are implemented in C/C++ to ensure fast performance.

• Levenshtein(): Levenshtein distance/similarity
• DamerauLevenshtein() Damerau-Levenshtein distance/similarity
• Hamming(): Hamming distance/similarity
• OSA(): Optimal String Alignment distance/similarity
• LCS(): Longest Common Subsequence distance/similarity
• Jaro(): Jaro distance/similarity
• JaroWinkler(): Jaro-Winkler distance/similarity

Not yet implemented.

• MongeElkan(): Monge-Elkan similarity
• FuzzyTokenSet(): Fuzzy Token Set distance

• InVocabulary(): Compares strings using a reference vocabulary. Useful for comparing names.
• Lookup(): Retrieves distances/similarities from a lookup table
• BinaryComp(): Compares strings based on whether they agree/disagree exactly.

• Euclidean(): Euclidean (L-2) distance
• Manhattan(): Manhattan (L-1) distance
• Chebyshev(): Chebyshev (L-∞) distance
• Minkowski(): Minkowski (L-p) distance

You can install the latest release from CRAN by entering:

install.packages("comparator")

The development version can be installed from GitHub using devtools:

# install.packages("devtools")
devtools::install_github("ngmarchant/comparator")

A comparator is instantiated by calling its constructor function. For example, we can instantiate a Levenshtein similarity comparator that ignores differences in upper/lowercase characters as follows:

comparator <- Levenshtein(similarity = TRUE, normalize = TRUE, ignore_case = TRUE)

We can apply the comparator to character vectors element-wise as follows:

x <- c("John Doe", "Jane Doe")
y <- c("jonathon doe", "jane doe")
elementwise(comparator, x, y)
#> [1] 0.6666667 1.0000000

# shorthand for above
comparator(x, y)
#> [1] 0.6666667 1.0000000

This comparator is also defined on sequences:

x_seq <- list(c(1, 2, 1, 1), c(1, 2, 3, 4))
y_seq <- list(c(4, 3, 2, 1), c(1, 2, 3, 1))
elementwise(comparator, x_seq, y_seq)
#> [1] 0.4545455 0.7777778

# shorthand for above
comparator(x_seq, y_seq)
#> [1] 0.4545455 0.7777778

Pairwise comparisons are also supported using the following syntax:

# compare each string in x with each string in y and return a similarity matrix
pairwise(comparator, x, y, return_matrix = TRUE)
#>           [,1]      [,2]
#> [1,] 0.6666667 0.6842105
#> [2,] 0.5384615 1.0000000

# compare the strings in x pairwise and return a similarity matrix
pairwise(comparator, x, return_matrix = TRUE)
#>           [,1]      [,2]
#> [1,] 1.0000000 0.6842105
#> [2,] 0.6842105 1.0000000