R 有没有办法限制IML包Shapley值中的功能数量？

我有一个用H2O包创建的automl模型。目前，H2O仅在基于树的模型上计算Shapley值。我已经使用IML软件包来计算AML模型上的值。然而，因为我有大量的功能，情节太混乱，无法阅读。我正在寻找一种只选择/显示前X个功能的方法。我在IML CRAN PDF或谷歌搜索到的其他文档中找不到任何内容

#initiate h2o
h2o.init()
h2o.no_progress()

#create automl model (data cleaning and train/test split not shown)
set.seed(1911)
num_models <- 10
aml <- h2o.automl(y = label, x = features,
                   training_frame = train.hex,
                   nfolds = 5,
                   balance_classes = TRUE,
                   leaderboard_frame = test.hex,
                   sort_metric = 'AUCPR',
                   max_models = num_models,
                   verbosity = 'info',
                   exclude_algos = "DeepLearning", #exclude for reproducibility
                   seed = 27)

# 1. create a data frame with just the features
features_eval <- as.data.frame(test) %>% dplyr::select(-target)

# 2. Create a vector with the actual responses
response <- as.numeric(as.vector(test$target))

# 3. Create custom predict function that returns the predicted values as a
#    vector (probability of purchasing in our example)
pred <- function(model, newdata)  {
  results <- as.data.frame(h2o.predict(model, as.h2o(newdata)))
  return(results[[3L]])
}

# example of prediction output
pred(aml, features_eval) %>% head()

#create predictor needed
predictor.aml <- Predictor$new(
  model = aml, 
  data = features_eval, 
  y = response, 
  predict.fun = pred,
  class = "classification"
  )

high <- predict(aml, test.hex) %>% .[,3] %>% as.vector() %>% which.max()

high_prob_ob <- features_eval[high, ]

shapley <- Shapley$new(predictor.aml, x.interest = high_prob_ob, sample.size = 200) 

plot(shapley, sort = TRUE)

#启动h2o
h2o.init（）
h2o.无进展（）
#创建automl模型（未显示数据清理和训练/测试分割）
种子集（1911）
num_models我可以提供一个黑客解决方案，利用
iml
使用
ggplot2
进行绘图

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