For some models, the effectiveness of the model can decrease as training iterations continue. stop_iter() can be used to tune how many iterations without an improvement in the objective function occur before training should be halted.

## Usage

stop_iter(range = c(3L, 20L), 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.

## Examples

stop_iter()
#> # Iterations Before Stopping (quantitative)
#> Range: [3, 20]