Dataframe with rules used by f_auto() to select the function f in f_functions() to compute preference order in preference_order(). In most cases, random forest is selected as base model to provide homogeneous results across case types.
See also
Other preference_order_tools:
f_auto(),
f_functions()
Examples
f_auto_rules()
#> name response_type predictors_type
#> 1 f_numeric_glm continuous-binary numeric
#> 2 f_numeric_rf continuous-binary categorical
#> 3 f_numeric_rf continuous-binary mixed
#> 4 f_numeric_glm continuous-low numeric
#> 5 f_numeric_rf continuous-low categorical
#> 6 f_numeric_rf continuous-low mixed
#> 7 f_numeric_glm continuous-high numeric
#> 8 f_numeric_rf continuous-high categorical
#> 9 f_numeric_rf continuous-high mixed
#> 10 f_binomial_glm integer-binomial numeric
#> 11 f_binomial_rf integer-binomial categorical
#> 12 f_binomial_rf integer-binomial mixed
#> 13 f_count_glm integer-binary numeric
#> 14 f_count_rf integer-binary categorical
#> 15 f_count_rf integer-binary mixed
#> 16 f_count_glm integer-low numeric
#> 17 f_count_rf integer-low categorical
#> 18 f_count_rf integer-low mixed
#> 19 f_count_glm integer-high numeric
#> 20 f_count_rf integer-high categorical
#> 21 f_count_rf integer-high mixed
#> 22 f_categorical_rf categorical numeric
#> 23 f_categorical_rf categorical mixed
#> 24 f_categorical_rf categorical categorical