| distance {fingerprint} | R Documentation |
A number of distance metrics can be calculated for binary fingerprints. These metrics can be used to evaluate similarity/dissimilarity between fingerprints and hence are useful for clustering purposes. The function currently allows the evaluation of 4 distance metrics
distance(fp1, fp2, method)
fp1 |
An object of class fingerprint
|
fp2 |
An object of class fingerprint
|
method |
The type of distance metric desired. Alternative values are
euclidean and dice and mt. Partial matching
is supported and the deault is tanimoto
|
Numeric value representing the distance in the specified metric between the supplied fingerprint objects
Rajarshi Guha rguha@indiana.edu
Fligner, M.A.; Verducci, J.S.; Blower, P.E.; A Modification of the Jaccard-Tanimoto Similarity Index for Diverse Selection of Chemical Compounds Using Binary Strings, Technometrics, 2002, 44(2), 110-119
# make a 2 fingerprint vectors
fp1 <- new("fingerprint", nbit=6, bits=c(1,2,5,6))
fp2 <- new("fingerprint", nbit=6, bits=c(1,2,5,6))
# calculate the tanimoto coefficient
distance(fp1,fp2) # should be 1
# Invert the second fingerprint
fp3 <- !fp2
distance(fp1,fp3) # should be 0