Feature selection recipes allow the top-performing features to be selected using three parameters. `top_p` is for specifying the number of the top-performing features.
Usage
top_p(range = c(1L, 4L), 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
top_p(c(3, 10))
#> # Selected Predictors (quantitative)
#> Range: [3, 10]