Test one or more classifier models against held-out dataset Using held-out test features, evaluates the performance of the estimated model Can be part of a kubeflow pipeline as a test step that is run post EDA and training/validation cycles.
:param context: the function context
:param models_path: artifact models representing a file or a folder
:param test_set: test features and labels
:param label_column: column name for ground truth labels
:param score_method: for multiclass classification
:param plots_dest: dir for test plots
:param model_evaluator: NOT IMPLEMENTED: specific method to generate eval, passed in as string
or available in this folder
:param predictions_column: column name for the predictions column on the resulted artifact
:param model_update: (True) update model, when running as stand alone no need in update