Perform lumping on a hierarchical nominal variable

Perform lumping on a hierarchical nominal variable

Usage

lump_hierarchical(
  data,
  threshold,
  clusters,
  verbose = FALSE,
  alternative_metric = c("mutual information", "bin count", "surplus"),
  level_namer = default_level_namer
)

Arguments

data

Factor or character vector of the categorical data.

threshold

The minimum number of samples each lumped level should contain.

clusters

List of character vectors representing the levels that are allowed to be lumped together.

verbose

Logical value dictating if values should be printed. Default: FALSE.

alternative_metric

The metric that should be optimised for, if it is different from the default, the mutual information. For an explanation of the metrics see vignette("metrics").

level_namer

Function that takes a character vector of the original levels in a lump and returns the name of the new lumped level. Default: concatenating the original levels with a "+" in between.

Value

A factor vector with the lumped levels.

See also

maximum_mutual_information_hierarchical() for the underlying algorithm that this function wraps.

lump_nominal() for a more general version of this function that does not need the hierarchical structure in the data, but may be slower.

Author

Daan Koning

Examples

country <- c("Germany", "Netherlands", "France", "France", "China", "China",
             "China", "China", "Vietnam", "Vietnam", "Japan", "Japan")
lump_hierarchical(
     country,
     4,
     list(c("Germany", "Netherlands", "France"), c("China", "Vietnam", "Japan"))
)
#>  [1] Germany+Netherlands+France Germany+Netherlands+France
#>  [3] Germany+Netherlands+France Germany+Netherlands+France
#>  [5] China                      China                     
#>  [7] China                      China                     
#>  [9] Vietnam+Japan              Vietnam+Japan             
#> [11] Vietnam+Japan              Vietnam+Japan             
#> Levels: Germany+Netherlands+France Vietnam+Japan China