hclus: Hierarchical cluster analysis

In radiant.multivariate: Multivariate Menu for Radiant: Business Analytics using R and Shiny

Hierarchical cluster analysis

Description

Hierarchical cluster analysis

Usage

hclus(
  dataset,
  vars,
  labels = "none",
  distance = "sq.euclidian",
  method = "ward.D",
  max_cases = 5000,
  standardize = TRUE,
  data_filter = "",
  envir = parent.frame()
)

Arguments

dataset	Dataset
vars	Vector of variables to include in the analysis
labels	A vector of labels for the leaves of the tree
distance	Distance
method	Method
max_cases	Maximum number of cases allowed (default is 1000). Set to avoid long-running analysis in the radiant web-interface
standardize	Standardized data (TRUE or FALSE)
data_filter	Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir	Environment to extract data from

Details

See https://radiant-rstats.github.io/docs/multivariate/hclus.html for an example in Radiant

Value

A list of all variables used in hclus as an object of class hclus

See Also

summary.hclus to summarize results

plot.hclus to plot results

Examples

hclus(shopping, vars = "v1:v6") %>% str()

radiant.multivariate documentation built on Sept. 23, 2023, 9:06 a.m.