Plot a two-dimensional cluster review map — PlotClusterMap • SciDataReportR

Cluster assignments in a two-dimensional review space. The space is frozen at training time and reused for projection so training and projected cases are directly comparable. It is a display space only and does not affect the clustering itself.

Usage

PlotClusterMap(
  data,
  x,
  y,
  ClusterVar = "Cluster",
  centroids = NULL,
  title = "Cluster review map",
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  noise_label = 0L
)

PlotClusterAssignment(data, x, y, ClusterVar = "Cluster")

Arguments

data: Data frame containing coordinates and a cluster column.
x, y: Coordinate variable names.
ClusterVar: Cluster column name.
centroids: Optional data frame of centroid coordinates in the same two columns, overlaid as crosses.
title, subtitle, xlab, ylab: Plot annotations.
noise_label: Cluster value treated as noise, or NULL to disable.

Value

A ggplot object.

Examples

# \donttest{
data(SimulatedPhenotypeData)
df_Training <- dplyr::filter(SimulatedPhenotypeData, .data$Cohort == "Training")
model <- CreateClusterModel_KMeans(
  df_Training, paste0("Var", 1:12), method = "finalize", final_k = 4
)
PlotClusterMap(model$DataWithClusters, "Var1", "Var2", "Cluster")

# }