last_fit 中的 Tidymodels/XGBoost 错误与 rsplit 值

Question

我正在尝试按照此处的教程进行操作 - https://juliasilge.com/blog/xgboost-tune-volleyball/

我在关于大湖捕鱼的最新 Tidy Tuesday 数据集上使用它 - 试图根据许多其他值来预测机构。

除了最后一行出现以下错误外，下面的所有代码都有效：

> final_res <- last_fit(final_xgb, stock_folds)
Error: Each element of `splits` must be an `rsplit` object.

我搜索了那个错误并来到了这个页面 - https://github.com/tidymodels/rsample/issues/175 该站点将其称为错误并且似乎已修复 - 但它是 initial_time_split，而不是我正在使用的 initial_split。我宁愿不更改它，因为那样我将不得不重新运行耗时 9 小时的 xgboost。这里出了什么问题？

# Setup ----
library(tidyverse)
library(tidymodels)

stocked <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-06-08/stocked.csv')

stocked_modeling <- stocked %>% 
  mutate(AGENCY = case_when(
    AGENCY != "OMNR" ~ "other",
    TRUE ~ AGENCY
  )) %>% 
  select(-SID, -MONTH, -DAY, -LATITUDE, -LONGITUDE, -GRID, -STRAIN, -AGEMONTH,
         -MARK_EFF, -TAG_NO, -TAG_RET, -LENGTH, -WEIGHT, - CONDITION, -LOT_CODE,
         -NOTES, - VALIDATION, -LS_MGMT, -STAT_DIST, -ST_SITE, -YEAR_CLASS, -STOCK_METH) %>% 
  mutate_if(is.character, factor) %>% 
  drop_na()

# Start making model ----
set.seed(123)
stock_split <- initial_split(stocked_modeling, strata = AGENCY)
stock_train <- training(stock_split)
stock_test <- testing(stock_split)

xgb_spec <- boost_tree(
  trees = 1000,
  tree_depth = tune(), min_n = tune(), loss_reduction = tune(),
  sample_size = tune(), mtry = tune(),
  learn_rate = tune()
) %>% 
  set_engine("xgboost") %>% 
  set_mode("classification")

xgb_grid <- grid_latin_hypercube(
  tree_depth(),
  min_n(),
  loss_reduction(),
  sample_size = sample_prop(),
  finalize(mtry(), stock_train),
  learn_rate(),
  size = 20
)

xgb_workflow <- workflow() %>% 
  add_formula(AGENCY ~ .) %>% 
  add_model(xgb_spec)

set.seed(123)
stock_folds <- vfold_cv(stock_train, strata = AGENCY)

doParallel::registerDoParallel()


# BEWARE, THIS CODE BELOW TOOK 9 HOURS TO RUN
set.seed(234)
xgb_res <- tune_grid(
  xgb_workflow,
  resamples = stock_folds,
  grid = xgb_grid,
  control = control_grid(save_pred = TRUE)
)

# Explore results
best_auc <- select_best(xgb_res, "roc_auc")

final_xgb <- finalize_workflow(
  xgb_workflow, 
  best_auc)

final_res <- last_fit(final_xgb, stock_folds)

Answer 1

如果我们查看 last_fit() 的文档，我们会发现 split 必须是

An rsplit object created from `rsample::initial_split().

您不小心将交叉验证折叠对象 stock_folds 传递给了 split 但您应该传递 rsplit 对象 stock_split 而不是

final_res <- last_fit(final_xgb, stock_split)

last_fit 中的 Tidymodels/XGBoost 错误与 rsplit 值

Tidymodels / XGBoost error in last_fit with rsplit value

r

xgboost

tidymodels