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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.

Usage

spruce_numeric(pred)

spruce_class(pred_class)

spruce_prob(pred_levels, prob_matrix)

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).