Parsnip Engine Entry Points

Exported entry points for the optional parsnip registration. Users should construct and predict with calibrated_workflow or model_adapter instead.

Usage

fit_vennabers(x, y, base_workflow, outcome, parameters, ...)
fit_vennabers_proxy(x, y, outcome, parameters, ...)
predict_vennabers_prob(object, new_data)
predict_vennabers_class(object, new_data)
predict_vennabers_numeric(object, new_data)

Arguments

x, y

Raw predictor data frame and factor classification or finite numeric regression truth from parsnip.

base_workflow

An unfitted configured base workflow.

outcome

Original outcome name.

parameters

Constructor-validated requested options and explicit flags, internal proxy candidate plans, or the validated callbacks of model_adapter (then base_workflow and outcome are unused).

...

Must be empty for fit_vennabers; an internal grid candidate ID or Bayes candidate values for fit_vennabers_proxy.

object

The fitted vennabers_fit, grid proxy or vennabers_adapter_fit engine state.

new_data

Forged raw predictors.

Value

The public fit entry point returns a vennabers_fit, or a vennabers_adapter_fit for adapter callbacks; the proxy returns a vennabers_grid_fit. Prediction entry points return a named probability tibble, factor of original classes, or double regression points.