Model predictions across many sub-models

# S3 method for class '`_brulee_auto_int`'
multi_predict(object, new_data, type = NULL, epochs = NULL, ...)

# S3 method for class '`_brulee_resnet`'
multi_predict(object, new_data, type = NULL, epochs = NULL, ...)

# S3 method for class '`_brulee_rln`'
multi_predict(object, new_data, type = NULL, epochs = NULL, ...)

Arguments

object

A model fit.

new_data

A rectangular data object, such as a data frame.

type

A single character value or NULL. Possible values are:

regression: "numeric"
classification: "class", "prob"
censored regression: "survival", "time", "hazard", "linear_pred"
quantile regression: "quantile"
interval estimates: "conf_int", "pred_int"
other: "raw"

When NULL, predict() will choose an appropriate value based on the model's mode.

epochs

An integer vector for the number of training epochs.

...

Optional arguments to pass to predict.model_fit(type = "raw") such as type.