plot.salso.summary {salso}

Heatmap, Multidimensional Scaling, Pairs, and Dendrogram Plotting for Partition Estimation

Description

This function produces one of four plots: 1. "heatmap": A heatmap showing the pairwise allocation probabilities that items are clustered. 2. "mds": A scatter plot using classical multidimensional scaling (also known as principal coordinates analysis) with the exemplar (i.e., the most representative observation) of each cluster emphasized. 3. "pairs": Pairs plots of all the variables with the exemplar (i.e., the most representative observation) of each cluster emphasized. 4. "dendrogram": A dendrogram based on expected partition loss showing the relationships among clusters when merging pairs of clusters such that the increase in the expectation of the posterior loss is minimized.

Usage

## S3 method for class 'salso.summary'
plot(
  x,
  type = c("heatmap", "mds", "pairs", "dendrogram")[1],
  data = NULL,
  showLabels = TRUE,
  showIDs = length(x$estimate) <= 50,
  ...
)

Arguments

x

An object returned by summary(y), where y itself is returned by the salso function.

type

A string equal to "heatmap", "mds", "pairs", or "dendrogram".

data

The data from which the partition estimation was obtained. This is required when type='pairs' and ignored otherwise.

showLabels

Should the cluster labels be shown in the plot when type="heatmap"?

showIDs

Should the ID of the items be shown in the plot?

...

Arguments to be passed to methods, such as graphical parameters (see par).

Value

NULL, invisibly.

See Also

salso, summary.salso.estimate, cmdscale.

Examples

# For examples, use 'nCores=1' per CRAN rules, but in practice omit this.
data(iris.clusterings)
draws <- iris.clusterings
# R_CARGO \dontrun{
# R_CARGO # Example disabled since Cargo was not found when installing from source package.
# R_CARGO # You can still run the example if you install Cargo. Hint: cargo::install().
est <- salso(draws, nCores=1)
summ <- summary(est)
plot(summ, type="heatmap")
plot(summ, type="mds")
plot(summ, type="pairs", data=iris)
plot(summ, type="dendrogram")
# R_CARGO }