Perform supervised lumping on an ordinal variable

Lumps the levels of an ordered categorical variable, combining only adjacent levels, so as to preserve as much mutual information as possible with a supplied outcome. The outcome may be discrete (a factor) or continuous (numeric); see vignette("supervised") for the distinction.

Usage

lump_ordinal_supervised(
  data,
  outcome,
  threshold,
  levels = NULL,
  verbose = FALSE,
  level_namer = default_level_namer,
  outcome_mode = c("auto", "discrete", "continuous")
)

Arguments

data

Factor or character vector of the categorical data.

outcome

Vector to be used as a source of information about data.

threshold

The minimum number of samples each lumped level should contain.

levels

Character vector specifying the strict ordinal hierarchy of the levels (from lowest to highest). Required if data is not already an ordered factor.

verbose

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

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.

outcome_mode

Whether to treat the outcome as discrete or continuous. Default: inferred based on the type of outcome.

Value

An ordered factor vector with the lumped levels.

See also

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

lump_ordinal() for the unsupervised version of this function.

Author

Daan Koning

Examples

# Discrete outcomes:
data    <- c("Low", "Medium", "Low", "High", "Medium",
             "Medium", "High", "High", "Low", "High")
outcome <- c(  0,      1,       0,     1,      1,
               0,      1,       1,     0,      1)
outcome <- factor(outcome)
lump_ordinal_supervised(data, outcome, threshold = 4,
                        levels = c("Low", "Medium", "High"))
#>  [1] Low+Medium Low+Medium Low+Medium High       Low+Medium Low+Medium
#>  [7] High       High       Low+Medium High      
#> Levels: Low+Medium < High

# It is also possible to directly pass ordered data:
data <- ordered(data, levels = c("Low", "Medium", "High"))
lump_ordinal_supervised(data, outcome, threshold = 4)
#>  [1] Low+Medium Low+Medium Low+Medium High       Low+Medium Low+Medium
#>  [7] High       High       Low+Medium High      
#> Levels: Low+Medium < High

# Alternatively, use a continuous outcome variable:
data <- c(rep("Low", 10), rep("Medium", 4), rep("High", 5))
n <- length(data)
outcome <- rnorm(n, mean = ifelse(data == "High", 10, 0))
lump_ordinal_supervised(data, outcome, threshold = 5,
                        levels = c("Low", "Medium", "High"))
#>  [1] Low+Medium Low+Medium Low+Medium Low+Medium Low+Medium Low+Medium
#>  [7] Low+Medium Low+Medium Low+Medium Low+Medium Low+Medium Low+Medium
#> [13] Low+Medium Low+Medium High       High       High       High      
#> [19] High      
#> Levels: Low+Medium < High