cluster_terms | R Documentation |
Cluster functional terms
cluster_terms(mat, method = "binary_cut", control = list(), catch_error = FALSE,
verbose = TRUE)
mat |
A similarity matrix. |
method |
Method for clustering the matrix. |
control |
A list of parameters passed to the corresponding clustering function. |
catch_error |
Internally used. |
verbose |
Whether to print messages. |
The following methods are the default:
kmeans
see cluster_by_kmeans
.
pam
see cluster_by_pam
.
dynamicTreeCut
see cluster_by_dynamicTreeCut
.
mclust
see cluster_by_mclust
.
apcluster
see cluster_by_apcluster
.
hdbscan
see cluster_by_hdbscan
.
leading_eigen
see cluster_by_igraph
.
louvain
see cluster_by_igraph
.
walktrap
see cluster_by_igraph
.
MCL
see cluster_by_MCL
.
binary_cut
see binary_cut
.
Also the user-defined methods in all_clustering_methods
can be used here.
New clustering methods can be registered by register_clustering_methods
.
Please note it is better to directly call cluster_terms
for clustering while not the individual cluster_by_*
functions
because cluster_terms
does additional cluster label adjustment.
A numeric vector of cluster labels (in numeric).
If catch_error
is set to TRUE
and if the clustering produces an error,
the function returns a try-error
object.
# There is no example
NULL
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