This family of spruce_*_multiple() functions converts multi-outcome
predictions into a standardized format. They are generally called from a
prediction implementation function for the specific type of prediction to
return.
Arguments
- ...
Multiple vectors of predictions:
For
spruce_numeric_multiple(), numeric vectors of equal size.For
spruce_class_multiple(), factors of "hard" class predictions of equal size.For
spruce_prob_multiple(), tibbles of equal size, which are the result of callingspruce_prob()on each matrix of prediction probabilities.
If the
...are named, then this name will be used as the suffix on the resulting column name, otherwise a positional index will be used.
Value
For
spruce_numeric_multiple(), a tibble of numeric columns named with the pattern.pred_*.For
spruce_class_multiple(), a tibble of factor columns named with the pattern.pred_class_*.For
spruce_prob_multiple(), a tibble of data frame columns named with the pattern.pred_*.
Examples
spruce_numeric_multiple(1:3, foo = 2:4)
#> # A tibble: 3 × 2
#> .pred_1 .pred_foo
#> <int> <int>
#> 1 1 2
#> 2 2 3
#> 3 3 4
spruce_class_multiple(
one_step = factor(c("a", "b", "c")),
two_step = factor(c("a", "c", "c"))
)
#> # A tibble: 3 × 2
#> .pred_class_one_step .pred_class_two_step
#> <fct> <fct>
#> 1 a a
#> 2 b c
#> 3 c c
one_step <- matrix(c(.3, .7, .0, .1, .3, .6), nrow = 2, byrow = TRUE)
two_step <- matrix(c(.2, .7, .1, .2, .4, .4), nrow = 2, byrow = TRUE)
binary <- matrix(c(.5, .5, .4, .6), nrow = 2, byrow = TRUE)
spruce_prob_multiple(
one_step = spruce_prob(c("a", "b", "c"), one_step),
two_step = spruce_prob(c("a", "b", "c"), two_step),
binary = spruce_prob(c("yes", "no"), binary)
)
#> # A tibble: 2 × 3
#> .pred_one_step$.pred_a .pred_two_step$.pred_a .pred_binary$.pred_yes
#> <dbl> <dbl> <dbl>
#> 1 0.3 0.2 0.5
#> 2 0.1 0.2 0.4
#> # ℹ 5 more variables: .pred_one_step$.pred_b <dbl>, $.pred_c <dbl>,
#> # .pred_two_step$.pred_b <dbl>, $.pred_c <dbl>,
#> # .pred_binary$.pred_no <dbl>