cluster_subnetwork

At the moment the only supported clustering algorithm is Louvain. Louvain tries to identify the communities in a network by optimizing the modularity of the whole network, that is a measure of the density of edges inside communities to edges outside communities. The result is a column of cluster IDs (integers), where the value -1 is reserved for nodes in very small clusters, which are grouped into a “noise” cluster.

cluster_subnetwork(ds_in: dataset, {
    "param": value,
    ...
}) -> (cluster: column)

targets

string (ds_in.column:list[number])

required

Name of column containing the link targets. Source is implied in the index.

weights

string (ds_in.column:list[number])

Name of column containing the link weights.

query

string

required

The graphext advanced query syntax used to select rows.

algorithm

string

default:"louvain"

Clustering algorithm to use.

Values must be one of the following:

louvain

resolution

number

default:"0.5"

The higher this value the bigger the clusters.

Values must be in the following range:

0 < resolution ≤ 1

noise

integer

default:"1"

The larger the value, the more conservative the clustering. Cluster with this number of nodes or less will be considered noise.

Values must be in the following range:

0 ≤ noise < inf

Prepare

Analyse

Report