Predict for a repeat ensemble set

Predict for a new dataset by using a repeat ensemble. Predictions from individual models are combined according to fun

Usage

# S3 method for class 'repeat_ensemble'
predict(
  object,
  new_data,
  type = "prob",
  fun = "mean",
  metric_thresh = NULL,
  class_thresh = NULL,
  members = FALSE,
  ...
)

Arguments

object

an repeat_ensemble object

new_data

a data frame in which to look for variables with which to predict.

type

the type of prediction, "prob" or "class".

fun

string defining the aggregating function. It can take values mean, median, weighted_mean, weighted_median and none. It is possible to combine multiple functions, except for "none". If it is set to "none", only the individual member predictions are returned (this automatically sets member to TRUE)

metric_thresh

a vector of length 2 giving a metric and its threshold, which will be used to prune which models in the ensemble will be used for the prediction. The 'metrics' need to have been computed when the workflow was tuned. Examples are c("accuracy",0.8) or c("boyce_cont",0.7)

class_thresh

probability threshold used to convert probabilities into classes. It can be a number (between 0 and 1), or a character metric (currently "tss_max" or "sensitivity"). For sensitivity, an additional target value is passed along as a second element of a vector, e.g. c("sensitivity",0.8).

members

boolean defining whether individual predictions for each member should be added to the ensemble prediction. The columns for individual members have the name of the workflow a a prefix, separated by "." from the usual column names of the predictions.

...

not used in this method.

Value

a tibble of predictions