Compares community structures using various metrics
This function assesses the distance between two community structures.
compare(comm1, comm2, method = c("vi", "nmi", "split.join", "rand", "adjusted.rand"))
communitiesobject containing a community structure; or a numeric vector, the membership vector of the first community structure. The membership vector should contain the community id of each vertex,
communitiesobject containing a community structure; or a numeric vector, the membership vector of the second community structure, in the same format as for the previous argument.
- Character scalar, the comparison method to use. Possible
viis the variation of information (VI) metric of Meila (2003), nmiis the normalized mutual information measure proposed by Danon et al. (2005), sp
- A real number.
Meila M: Comparing clusterings by the variation of information. In: Scholkopf B, Warmuth MK (eds.). Learning Theory and Kernel Machines: 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA. Lecture Notes in Computer Science, vol. 2777, Springer, 2003. ISBN: 978-3-540-40720-1.
Danon L, Diaz-Guilera A, Duch J, Arenas A: Comparing community structure identification. J Stat Mech P09008, 2005.
van Dongen S: Performance criteria for graph clustering and Markov cluster experiments. Technical Report INS-R0012, National Research Institute for Mathematics and Computer Science in the Netherlands, Amsterdam, May 2000.
Rand WM: Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66(336):846-850, 1971.
Hubert L and Arabie P: Comparing partitions. Journal of Classification 2:193-218, 1985.
g <- make_graph("Zachary") sg <- cluster_spinglass(g) le <- cluster_leading_eigen(g) compare(sg, le, method="rand") compare(membership(sg), membership(le))