Predict out-of-sample data — predict

Calculate predicted probabilities for out-of-sample dataset

Usage

predict_outsample(
  project,
  mod.name,
  outsample.mod.name,
  use.scalers = FALSE,
  scaler.func = NULL
)

project: Name of project
mod.name: Name of saved model to use. Argument can be the name of the model or can pull the name of the saved "best" model. Leave mod.name empty to use the saved "best" model. If more than one model is saved, mod.name should be the numeric indicator of which model to use. Use table_view("modelChosen", project) to view a table of saved models.
outsample.mod.name: Name of the saved out-of-sample model design.
use.scalers: Input for create_model_input(). Logical, should data be normalized? Defaults to FALSE. Rescaling factors are the mean of the numeric vector unless specified with scaler.func.
scaler.func: Input for create_model_input(). Function to calculate rescaling factors.

This function predicts out-of-sample fishing probabilities and calculates model prediction performance (percent absolute prediction error).

if (FALSE) {

predict_outsample("scallop1", "logit_c_mod1", "logit_c_mod1_outsample")

}