Assess multiple pairs of measured and predicted values — assess

Return performance metrics for test set predictions and measured values, e.g. for different model outcome variables.

assess_multimodels(
  data,
  ...,
  .metrics = c("simplerspec", "yardstick"),
  .model_name = "model"
)

Arguments

data: Data frame with all measured (observed) and predicted variables.
...: Multiple arguments with observed (measured)-predicted pairs, specified with dplyr::vars(o = <column_name>, p = <column_name>). Column names can strings or symbols. The arguments in ... need to be named.
.metrics: Character vector with package used for metrics calculation. Default is "simplerspec", which uses simplerspec::evaluate_model().
.model_name: String with name for the new column that specifies the model or the outcome variable. Default is "model".

Data frame with with summary statistics for measured values and performance metrics for the pairs of measured and predicted values.