Summary method for model importance score table

Usage

# S3 method for class 'model_imp_tbl'
summary(object, ...)

A list of class summary.model_imp_tbl with four elements:

all_models: A character vector of the unique model IDs present in object.
all_tasks: A data frame with one row per unique prediction task (one column per task ID, e.g. location, horizon, target_end_date).
model_summary: A data frame with one row per model and columns model_id, n_tasks (number of tasks the model was scored on), min_importance, max_importance, and n_NA (number of tasks with a missing importance score).
task_winners: A data frame with one row per prediction task and columns for the task ID(s), top_model (the model with the highest importance score for that task), and max_score (that model's importance score).

This object is printed via print.summary.model_imp_tbl.