.process_models_or_automl: Do basic validation and transform `object` to a "standardized" list containing models, and their properties such as `x`, `y`, whether it is a (multinomial) clasification or not etc.

Description

Do basic validation and transform object to a "standardized" list containing models, and their properties such as x, y, whether it is a (multinomial) clasification or not etc.

Usage

.process_models_or_automl(
  object,
  newdata,
  require_single_model = FALSE,
  require_multiple_models = FALSE,
  top_n_from_AutoML = NA,
  only_with_varimp = FALSE,
  best_of_family = FALSE,
  require_newdata = TRUE,
  check_x_y_consistency = TRUE
)

Value

a list with the following names leader, is_automl, models,

is_classification, is_multinomial_classification, x, y, model

Arguments

object: Can be a single model/model_id, vector of model_id, list of models, H2OAutoML object
newdata: An H2OFrame with the same format as training frame
require_single_model: If true, make sure we were provided only one model
require_multiple_models: If true, make sure we were provided at least two models
top_n_from_AutoML: If set, don't return more than top_n models (applies only for AutoML object)
only_with_varimp: If TRUE, return only models that have variable importance
best_of_family: If TRUE, return only the best of family models; if FALSE return all models in object
require_newdata: If TRUE, require newdata to be specified; otherwise allow NULL instead, this can be used when there is no need to know if the problem is (multinomial) classification.
check_x_y_consistency: If TRUE, make sure that when given a list of models all models have the same X and y. Defaults to TRUE.