cluster_network(targets: list[number], *weights: list[number], {
    "param": value,
    ...
}) -> (cluster: column)

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_network(targets: list[number], *weights: list[number], {
    "param": value,
    ...
}) -> (cluster: column)
​
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
​
query
string

The graphext advanced query syntax used to select rows.

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