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.
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.
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.
Returns
a list with the following names leader, is_automl, models, is_classification, is_multinomial_classification, x, y, model