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Tidymodels：如何从训练数据中提取重要性

我有以下代码，其中我对不同的 mtry 和 min_n 进行一些网格搜索。我知道如何提取提供最高准确度的参数（请参阅第二个代码框）。如何提取训练数据集中每个特征的重要性？我在网上找到的指南显示了如何使用“last_fit”仅在测试数据集中执行此操作。例如指南：https: //www.tidymodels.org/start/case-study/#data-split

set.seed(seed_number)
    data_split <- initial_split(node_strength,prop = 0.8,strata = Group)
    
    train <- training(data_split)
    test <- testing(data_split)
    train_folds <- vfold_cv(train,v = 10)
    
    
    rfc <- rand_forest(mode = "classification", mtry = tune(),
                       min_n = tune(), trees = 1500) %>%
        set_engine("ranger", num.threads = 48, importance = "impurity")
    
    rfc_recipe <- recipe(data = train, Group~.)
    
    rfc_workflow <- workflow() %>% add_model(rfc) %>%
        add_recipe(rfc_recipe)
    
    rfc_result <- rfc_workflow %>%
        tune_grid(train_folds, grid = 40, control = control_grid(save_pred = TRUE),
                  metrics = metric_set(accuracy))

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