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.
spruce_numeric(pred)spruce_class(pred_class)
spruce_prob(pred_levels, prob_matrix)
(type = "numeric"
) A numeric vector of predictions.
(type = "class"
) A factor of "hard" class predictions.
(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.
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.
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
).