get_clusters: get_clusters

In clustNet: Network-Based Clustering

get_clusters

Description

Network-based clustering

Usage

get_clusters(
  myData,
  k_clust = 3,
  n_bg = 0,
  quick = TRUE,
  EMseeds = 1,
  edgepmat = NULL,
  blacklist = NULL,
  bdepar = list(chi = 0.5, edgepf = 8),
  newallrelativeprobabs = NULL
)

Arguments

myData	Data to be clustered, must be either binary (with levels "0"/"1") or categorical (with levels "0"/"1"/"2"/...)
k_clust	Number of clusters
n_bg	Number of covariates to be adjusted for; the position of the covariates must be in the last column of the myData matrix
quick	if TRUE, then the runtime is quick but accuracy is lower
EMseeds	Seeds
edgepmat	Matrix of penalized edges in the search space
blacklist	Matrix of forbidden edges in the search space
bdepar	Hyperparameters for structure learning (BDE score)
newallrelativeprobabs	relative probability of cluster assignment of each sample

Value

a list containing the clusterMemberships and "assignprogress"

Examples

# choose data
sampled_data <- sampleData(n_vars = 15, n_samples = c(300,300,300))$sampled_data
# learn clusters
cluster_results <- get_clusters(sampled_data)
# visualize the networks
library(ggplot2)
library(ggraph)
library(igraph)
library(ggpubr)
plot_clusters(cluster_results)

clustNet documentation built on May 29, 2024, 12:13 p.m.