当我试图提取用R中的ranger包构建的回归模型的估计值时，我得到了错误消息Error: No tidy method for objects of class ranger。
下面是我的代码：

# libraries
library(tidymodels)
library(textrecipes)
library(LiblineaR)
library(ranger)
library(tidytext)

# create the recipe
comments.rec <- recipe(year ~ comments, data = oa.comments) %>%
  step_tokenize(comments, token = "ngrams", options = list(n = 2, n_min = 1)) %>%
  step_tokenfilter(comments, max_tokens = 1e3) %>%
  step_stopwords(comments, stopword_source = "stopwords-iso") %>%
  step_tfidf(comments) %>%
  step_normalize(all_predictors())

# workflow with recipe
comments.wf <- workflow() %>%
  add_recipe(comments.rec)

# create the regression model using support vector machine
svm.spec <- svm_linear() %>%
  set_engine("LiblineaR") %>%
  set_mode("regression")

svm.fit <- comments.wf %>%
  add_model(svm.spec) %>%
  fit(data = oa.comments)

# extract the estimates for the support vector machine model
svm.fit %>%
  pull_workflow_fit() %>%
  tidy() %>%
  arrange(-estimate)

下面是数据集中每个标记化术语的估计值表（这是用于演示目的的脏数据集）

term                     estimate
   <chr>                       <dbl>
 1 Bias                     2015.   
 2 tfidf_comments_2021         0.877
 3 tfidf_comments_2019         0.851
 4 tfidf_comments_2020         0.712
 5 tfidf_comments_2018         0.641
 6 tfidf_comments_https        0.596
 7 tfidf_comments_plan s       0.462
 8 tfidf_comments_plan         0.417
 9 tfidf_comments_2017         0.399
10 tfidf_comments_libraries    0.286

但是，当使用ranger引擎从随机森林创建回归模型时，我就没有这样的运气了，并得到了上面的错误消息

# create the regression model using random forests
rf.spec <- rand_forest(trees = 50) %>%
  set_engine("ranger") %>%
  set_mode("regression")

rf.fit <- comments.wf %>%
  add_model(rf.spec) %>%
  fit(data = oa.comments)

# extract the estimates for the random forests model
rf.fit %>%
  pull_workflow_fit() %>%
  tidy() %>%
  arrange(-estimate)