View a Single Output of a Multi-Output kerasnip Fit

tailor and probably are built around models with a single outcome column and a single .pred/.pred_class prediction column. A kerasnip multi-output model (e.g. a recipe with output_1 + output_2 ~ .) instead produces .pred_output_1, .pred_output_2, ... columns from multiple truth columns in one fit — the standard parsnip::maybe_multivariate() shape, but one tailor::fit()/workflows::add_tailor() call cannot consume it (it selects outcome/estimate via [[, which requires exactly one column).

kerasnip_output_view() wraps a fitted multi-output workflow together with one output name, presenting it as if it were an ordinary single-output fit: predict() returns standard .pred / .pred_class / .pred_<level> columns for that output alone, letting you calibrate or post-process each output separately with the usual tailor/probably calls (see vignette("multi_output_postprocessing")).

Usage

kerasnip_output_view(x, output)

Arguments

x

A fitted (trained) workflow whose model has more than one outcome column.

output

A string, the name of the outcome column to view.

Value

A kerasnip_output_view object.

Examples

if (FALSE) { # \dontrun{
fit_obj <- fit(wf, data = train_data) # wf predicts output_1 and output_2
view_1 <- kerasnip_output_view(fit_obj, "output_1")
predict(view_1, new_data = test_data) # -> a single `.pred` column
} # }