These parameters are auxiliary to tree-based models that use the "C5.0" engine. They correspond to tuning parameters that would be specified using set_engine("C5.0", ...).

confidence_factor(range = c(-1, 0), trans = log10_trans())

no_global_pruning(values = c(TRUE, FALSE))

predictor_winnowing(values = c(TRUE, FALSE))

fuzzy_thresholding(values = c(TRUE, FALSE))

rule_bands(range = c(2L, 500L), trans = NULL)

Arguments

range

A two-element vector holding the defaults for the smallest and largest possible values, respectively.

trans

A trans object from the scales package, such as scales::log10_trans() or scales::reciprocal_trans(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

values

For no_global_pruning(), predictor_winnowing(), and fuzzy_thresholding() either TRUE or FALSE.

Details

To use these, check ?C50::C5.0Control to see how they are used.

Examples

confidence_factor()
#> Confidence Factor for Splitting (quantitative) #> Transformer: log-10 #> Range (transformed scale): [-1, 0]
no_global_pruning()
#> Skip Global Pruning? (qualitative) #> 2 possible value include: #> TRUE and FALSE
predictor_winnowing()
#> Use Initial Feature Selection? (qualitative) #> 2 possible value include: #> TRUE and FALSE
fuzzy_thresholding()
#> Use Fuzzy Thresholding? (qualitative) #> 2 possible value include: #> TRUE and FALSE
rule_bands()
#> Number of Rule Bands (quantitative) #> Range: [2, 500]