The family of `spruce_*()`

functions convert predictions into a
standardized format. They are generally called from a prediction
implementation function for the specific `type`

of prediction to return.

## Arguments

- pred
(

`type = "numeric"`

) A numeric vector of predictions.- pred_class
(

`type = "class"`

) A factor of "hard" class predictions.- pred_levels, prob_matrix
(

`type = "prob"`

)`pred_levels`

should be a character vector of the original levels of the outcome used in training.`prob_matrix`

should be a numeric matrix of class probabilities with as many columns as levels in`pred_levels`

, and in the same order.

## Value

A tibble, ideally with the same number of rows as the `new_data`

passed
to `predict()`

. The column names and number of columns vary based on the
function used, but are standardized.

## Details

After running a `spruce_*()`

function, you should *always* use the validation
function `validate_prediction_size()`

to ensure that the number of rows
being returned is the same as the number of rows in the input (`new_data`

).