equivalence {migraph} | R Documentation |
Equivalence clustering algorithms
Description
These functions combine an appropriate _census()
function
together with methods for calculating the hierarchical clusters
provided by a certain distance calculation.
-
node_equivalence()
assigns nodes membership based on their equivalence with respective to some census/class. The following functions call this function, together with an appropriate census.-
node_structural_equivalence()
assigns nodes membership based on their having equivalent ties to the same other nodes. -
node_regular_equivalence()
assigns nodes membership based on their having equivalent patterns of ties. -
node_automorphic_equivalence()
assigns nodes membership based on their having equivalent distances to other nodes.
-
A plot()
method exists for investigating the dendrogram
of the hierarchical cluster and showing the returned cluster
assignment.
Usage
node_equivalence(
.data,
census,
k = c("silhouette", "elbow", "strict"),
cluster = c("hierarchical", "concor"),
distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
range = 8L
)
node_structural_equivalence(
.data,
k = c("silhouette", "elbow", "strict"),
cluster = c("hierarchical", "concor"),
distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
range = 8L
)
node_regular_equivalence(
.data,
k = c("silhouette", "elbow", "strict"),
cluster = c("hierarchical", "concor"),
distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
range = 8L
)
node_automorphic_equivalence(
.data,
k = c("silhouette", "elbow", "strict"),
cluster = c("hierarchical", "concor"),
distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
range = 8L
)
Arguments
.data |
An object of a
|
census |
A matrix returned by a |
k |
Typically a character string indicating which method
should be used to select the number of clusters to return.
By default |
cluster |
Character string indicating whether clusters should be
clustered hierarchically ( |
distance |
Character string indicating which distance metric
to pass on to |
range |
Integer indicating the maximum number of (k) clusters
to evaluate.
Ignored when |
Source
https://github.com/aslez/concoR
See Also
Other memberships:
cliques
,
community
,
components()
,
core
Examples
(nse <- node_structural_equivalence(mpn_elite_usa_advice))
plot(nse)
(nre <- node_regular_equivalence(mpn_elite_usa_advice,
cluster = "concor"))
plot(nre)
(nae <- node_automorphic_equivalence(mpn_elite_usa_advice,
k = "elbow"))
plot(nae)