compare | R Documentation |
This function assesses the distance between two community structures.
compare(
comm1,
comm2,
method = c("vi", "nmi", "split.join", "rand", "adjusted.rand")
)
comm1 |
A |
comm2 |
A |
method |
Character scalar, the comparison method to use. Possible values: ‘vi’ is the variation of information (VI) metric of Meila (2003), ‘nmi’ is the normalized mutual information measure proposed by Danon et al. (2005), ‘split.join’ is the split-join distance of can Dongen (2000), ‘rand’ is the Rand index of Rand (1971), ‘adjusted.rand’ is the adjusted Rand index by Hubert and Arabie (1985). |
A real number.
Tamas Nepusz ntamas@gmail.com
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.
Community detection
as_membership()
,
cluster_edge_betweenness()
,
cluster_fast_greedy()
,
cluster_fluid_communities()
,
cluster_infomap()
,
cluster_label_prop()
,
cluster_leading_eigen()
,
cluster_leiden()
,
cluster_louvain()
,
cluster_optimal()
,
cluster_spinglass()
,
cluster_walktrap()
,
groups()
,
make_clusters()
,
membership()
,
modularity.igraph()
,
plot_dendrogram()
,
split_join_distance()
,
voronoi_cells()
g <- make_graph("Zachary")
sg <- cluster_spinglass(g)
le <- cluster_leading_eigen(g)
compare(sg, le, method = "rand")
compare(membership(sg), membership(le))
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