
Plots for Hierarchical Clustering Learners
Source:R/LearnerClustHierarchical.R
      autoplot.LearnerClustHierarchical.RdVisualizations for hierarchical clusters.
The argument type controls what kind of plot is drawn.
Possible choices are:
- "dend"(default): Dendrograms using ggdendro package.
- "scree": Scree plot that shows the number of possible clusters on the x-axis and the height on the y-axis.
Usage
# S3 method for class 'LearnerClustHierarchical'
autoplot(
  object,
  type = "dend",
  task = NULL,
  theme = theme_minimal(),
  theme_dendro = TRUE,
  ...
)Arguments
- object
- (mlr3cluster::LearnerClustAgnes | mlr3cluster::LearnerClustDiana | mlr3cluster::LearnerClustHclust). 
- type
- (character(1)): 
 Type of the plot. See description.
- task
- (mlr3::Task) 
 Optionally, pass the task to add labels of observations to a- hclustdendrogram. Labels are set via the row names of the task.
- theme
- ( - ggplot2::theme())
 The- ggplot2::theme_minimal()is applied by default to all plots.
- theme_dendro
- ( - logical(1))
 If- TRUE(default), the special dendrogram theme from ggdendro package is used in plot- "dend". Set to- FALSEto use the theme passed in- theme.
- ...
- (ignored). 
Examples
if (requireNamespace("mlr3")) {
  library(mlr3)
  library(mlr3cluster)
  library(mlr3viz)
  task = tsk("usarrests")
  # agnes clustering
  learner = lrn("clust.agnes")
  learner$train(task)
  autoplot(learner)
  # diana clustering
  learner = lrn("clust.diana")
  learner$train(task)
  autoplot(learner)
  # hclust clustering
  learner = lrn("clust.hclust")
  learner$train(task)
  autoplot(learner, type = "scree")
}
