extract_model_vimp: Internal function to extract variable importance from models.

Description

Aggregate variable importance from models in a familiarEnsemble.

Usage

extract_model_vimp(
  object,
  data,
  aggregation_method = waiver(),
  rank_threshold = waiver(),
  message_indent = 0L,
  verbose = FALSE,
  ...
)

Value

A list containing variable importance information.

Arguments

object

A familiarEnsemble object, which is an ensemble of one or more familiarModel objects.

data

A dataObject object, data.table or data.frame that constitutes the data that are assessed.

aggregation_method

Method for aggregating variable importances for the purpose of evaluation. Variable importances are determined during feature selection steps and after training the model. Both types are evaluated, but feature selection variable importance is only evaluated at run-time.

See the documentation for the vimp_aggregation_method argument in summon_familiar for information concerning the different available methods.

If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.

rank_threshold

The threshold used to define the subset of highly important features during evaluation.

See the documentation for the vimp_aggregation_rank_threshold argument in summon_familiar for more information.

If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.

message_indent

Number of indentation steps for messages shown during computation and extraction of various data elements.

verbose

Flag to indicate whether feedback should be provided on the computation and extraction of various data elements.

...

Unused arguments.