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.
Source: R/explain.R
dot-process_models_or_automl.RdDo 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
)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.