Binning Algorithm Parameter

A qualitative tuning parameter for selecting the optimal binning algorithm in step_obwoe.

Usage

obwoe_algorithm(values = NULL)

Arguments

values

A character vector of algorithm names to include in the parameter space. If NULL (default), includes all 29 algorithms (28 specific algorithms plus "auto").

Value

A dials qualitative parameter object.

Details

The algorithms are organized into three groups:

Universal (support both numerical and categorical features): "auto", "jedi", "jedi_mwoe", "cm", "dp", "dmiv", "fetb", "mob", "sketch", "udt"

Numerical only: "bb", "ewb", "fast_mdlp", "ir", "kmb", "ldb", "lpdb", "mblp", "mdlp", "mrblp", "oslp", "ubsd"

Categorical only: "gmb", "ivb", "mba", "milp", "sab", "sblp", "swb"

When tuning with mixed feature types, consider restricting values to universal algorithms only.

See also

step_obwoe, obwoe

Examples

# Default: all algorithms
obwoe_algorithm()
#> Binning Algorithm (qualitative)
#> 29 possible values include:
#> 'auto', 'jedi', 'jedi_mwoe', 'cm', 'dp', 'dmiv', 'fetb', 'mob', 'sketch',
#> 'udt', 'gmb', 'ivb', 'mba', 'milp', 'sab', 'sblp', 'swb', 'bb', …, 'oslp', and
#> 'ubsd'

# Restrict to universal algorithms for mixed data
obwoe_algorithm(values = c("jedi", "mob", "dp", "cm"))
#> Binning Algorithm (qualitative)
#> 4 possible values include:
#> 'jedi', 'mob', 'dp', and 'cm'

# Numerical-only algorithms
obwoe_algorithm(values = c("mdlp", "fast_mdlp", "ewb", "ir"))
#> Binning Algorithm (qualitative)
#> 4 possible values include:
#> 'mdlp', 'fast_mdlp', 'ewb', and 'ir'