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Bin Cutoff Parameter

Source: R/step_obwoe.R
obwoe_bin_cutoff.Rd

A quantitative tuning parameter for the minimum bin support (proportion of observations per bin) in step_obwoe.

Usage

obwoe_bin_cutoff(range = c(0.01, 0.1), trans = NULL)

Arguments

range

A two-element numeric vector specifying the minimum and maximum values for the parameter. Default is c(0.01, 0.10).

trans

A transformation object from the scales package, or NULL for no transformation. Default is NULL.

Value

A dials quantitative parameter object.

Details

The bin cutoff specifies the minimum proportion of observations that each bin must contain. Bins with fewer observations are merged with adjacent bins. This serves as a regularization mechanism:

  • Lower values (e.g., 0.01) allow smaller bins, capturing subtle patterns but risking unstable WoE estimates.

  • Higher values (e.g., 0.10) enforce larger bins, producing more stable estimates but potentially missing important patterns.

For credit scoring, values between 0.02 and 0.05 are typical. Regulatory guidelines often require minimum bin sizes for model stability.

See also

step_obwoe, control.obwoe

Examples

obwoe_bin_cutoff()
#> Bin Support Cutoff (quantitative)
#> Range: [0.01, 0.1]
obwoe_bin_cutoff(range = c(0.02, 0.08))
#> Bin Support Cutoff (quantitative)
#> Range: [0.02, 0.08]