UseMethod("required_pkgs") 错误：没有适用于 'required_pkgs' 的方法应用于 class "workflow" 的对象
Error in UseMethod("required_pkgs") : no applicable method for 'required_pkgs' applied to an object of class "workflow"
我正在关注 Jan Kirenz tutorial 使用 Tidymodel 进行分类。到目前为止一切顺利，直到我尝试使用函数 fit_resamples() 评估模型。我不断收到错误消息 Error in UseMethod("required_pkgs") : no applicable method for 'required_pkgs' applied to an object of class "workflow" .
他在该部分使用的代码是：
log_res <-
log_wflow %>%
fit_resamples(
resamples = cv_folds,
metrics = metric_set(
recall, precision, f_meas,
accuracy, kap,
roc_auc, sens, spec),
control = control_resamples(
save_pred = TRUE)
)
我尝试使用函数 documentation page 中的示例，但我收到了相同的错误消息。
library(tidymodels)
set.seed(6735)
folds <- vfold_cv(mtcars, v = 5)
spline_rec <- recipe(mpg ~ ., data = mtcars) %>%
step_ns(disp) %>%
step_ns(wt)
lin_mod <- linear_reg() %>%
set_engine("lm")
control <- control_resamples(save_pred = TRUE)
spline_res <- fit_resamples(lin_mod, spline_rec, folds, control = control)
#Error in UseMethod("required_pkgs") : no applicable method for 'required_pkgs' applied to an object of class "workflow"
有谁知道这里的问题是什么，我该如何解决？我找不到任何关于此问题的提及。
这是我的 sessionInfo():
R version 4.1.1 (2021-08-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
Random number generation:
RNG: Mersenne-Twister
Normal: Inversion
Sample: Rounding
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] workflowsets_0.1.0 tune_0.1.6 modeldata_0.1.1 infer_1.0.0 dials_0.0.9 scales_1.1.1 broom_0.7.9
[8] tidymodels_0.1.3 yardstick_0.0.8 GGally_2.1.2 keras_2.6.0 xgboost_1.4.1.1 ranger_0.13.1 parsnip_0.1.7
[15] recipes_0.1.16 workflows_0.2.3 rsample_0.1.0 skimr_2.1.3 visdat_0.5.3 gt_0.3.1 forcats_0.5.1
[22] stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4 readr_2.0.1 tidyr_1.1.3 tibble_3.1.4 ggplot2_3.3.5
[29] tidyverse_1.3.1
loaded via a namespace (and not attached):
[1] colorspace_2.0-2 ellipsis_0.3.2 class_7.3-19 base64enc_0.1-3 fs_1.5.0 rstudioapi_0.13 listenv_0.8.0
[8] furrr_0.2.3 farver_2.1.0 bit64_4.0.5 prodlim_2019.11.13 fansi_0.5.0 lubridate_1.7.10 xml2_1.3.2
[15] codetools_0.2-18 splines_4.1.1 knitr_1.33 zeallot_0.1.0 jsonlite_1.7.2 pROC_1.18.0 dbplyr_2.1.1
[22] png_0.1-7 tfruns_1.5.0 compiler_4.1.1 httr_1.4.2 backports_1.2.1 assertthat_0.2.1 Matrix_1.3-4
[29] fastmap_1.1.0 cli_3.0.1 htmltools_0.5.2 tools_4.1.1 gtable_0.3.0 glue_1.4.2 Rcpp_1.0.7
[36] DiceDesign_1.9 cellranger_1.1.0 vctrs_0.3.8 iterators_1.0.13 timeDate_3043.102 gower_0.2.2 xfun_0.25
[43] globals_0.14.0 rvest_1.0.1 lifecycle_1.0.0 future_1.22.1 MASS_7.3-54 ipred_0.9-11 vroom_1.5.4
[50] hms_1.1.0 parallel_4.1.1 RColorBrewer_1.1-2 yaml_2.2.1 curl_4.3.2 reticulate_1.20 sass_0.4.0
[57] rpart_4.1-15 reshape_0.8.8 stringi_1.7.4 tensorflow_2.6.0 foreach_1.5.1 checkmate_2.0.0 lhs_1.1.1
[64] hardhat_0.1.6 lava_1.6.10 repr_1.1.3 rlang_0.4.11 pkgconfig_2.0.3 lattice_0.20-44 labeling_0.4.2
[71] bit_4.0.4 tidyselect_1.1.1 parallelly_1.27.0 plyr_1.8.6 magrittr_2.0.1 R6_2.5.1 generics_0.1.0
[78] DBI_1.1.1 pillar_1.6.2 haven_2.4.3 whisker_0.4 withr_2.4.2 survival_3.2-11 nnet_7.3-16
[85] future.apply_1.8.1 modelr_0.1.8 crayon_1.4.1 utf8_1.2.2 tzdb_0.1.2 grid_4.1.1 readxl_1.3.1
[92] data.table_1.14.0 reprex_2.0.1 digest_0.6.27 GPfit_1.0-8 munsell_0.5.0
当我附加名为 tune 的包时，你问题中的第二个块工作正常。我认为通过 library(tidymodels) 包装器将 tidymodels 系列附加到您的工作区是一种更好的方法，而不是单独附加。
如果 tidymodels 包安装正确，（运行 a <- require(tidymodels) 和 a 应该合乎逻辑 TRUE）这段代码将起作用；
library(tidymodels)
set.seed(6735)
folds <- vfold_cv(mtcars, v = 5)
spline_rec <- recipe(mpg ~ ., data = mtcars) %>%
step_ns(disp) %>%
step_ns(wt)
lin_mod <- linear_reg() %>%
set_engine("lm")
control <- control_resamples(save_pred = TRUE)
spline_res <- fit_resamples(lin_mod, spline_rec, folds, control = control)
我正在关注 Jan Kirenz tutorial 使用 Tidymodel 进行分类。到目前为止一切顺利，直到我尝试使用函数 fit_resamples() 评估模型。我不断收到错误消息 Error in UseMethod("required_pkgs") : no applicable method for 'required_pkgs' applied to an object of class "workflow" .
他在该部分使用的代码是：
log_res <-
log_wflow %>%
fit_resamples(
resamples = cv_folds,
metrics = metric_set(
recall, precision, f_meas,
accuracy, kap,
roc_auc, sens, spec),
control = control_resamples(
save_pred = TRUE)
)
我尝试使用函数 documentation page 中的示例，但我收到了相同的错误消息。
library(tidymodels)
set.seed(6735)
folds <- vfold_cv(mtcars, v = 5)
spline_rec <- recipe(mpg ~ ., data = mtcars) %>%
step_ns(disp) %>%
step_ns(wt)
lin_mod <- linear_reg() %>%
set_engine("lm")
control <- control_resamples(save_pred = TRUE)
spline_res <- fit_resamples(lin_mod, spline_rec, folds, control = control)
#Error in UseMethod("required_pkgs") : no applicable method for 'required_pkgs' applied to an object of class "workflow"
有谁知道这里的问题是什么，我该如何解决？我找不到任何关于此问题的提及。
这是我的 sessionInfo():
R version 4.1.1 (2021-08-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
Random number generation:
RNG: Mersenne-Twister
Normal: Inversion
Sample: Rounding
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] workflowsets_0.1.0 tune_0.1.6 modeldata_0.1.1 infer_1.0.0 dials_0.0.9 scales_1.1.1 broom_0.7.9
[8] tidymodels_0.1.3 yardstick_0.0.8 GGally_2.1.2 keras_2.6.0 xgboost_1.4.1.1 ranger_0.13.1 parsnip_0.1.7
[15] recipes_0.1.16 workflows_0.2.3 rsample_0.1.0 skimr_2.1.3 visdat_0.5.3 gt_0.3.1 forcats_0.5.1
[22] stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4 readr_2.0.1 tidyr_1.1.3 tibble_3.1.4 ggplot2_3.3.5
[29] tidyverse_1.3.1
loaded via a namespace (and not attached):
[1] colorspace_2.0-2 ellipsis_0.3.2 class_7.3-19 base64enc_0.1-3 fs_1.5.0 rstudioapi_0.13 listenv_0.8.0
[8] furrr_0.2.3 farver_2.1.0 bit64_4.0.5 prodlim_2019.11.13 fansi_0.5.0 lubridate_1.7.10 xml2_1.3.2
[15] codetools_0.2-18 splines_4.1.1 knitr_1.33 zeallot_0.1.0 jsonlite_1.7.2 pROC_1.18.0 dbplyr_2.1.1
[22] png_0.1-7 tfruns_1.5.0 compiler_4.1.1 httr_1.4.2 backports_1.2.1 assertthat_0.2.1 Matrix_1.3-4
[29] fastmap_1.1.0 cli_3.0.1 htmltools_0.5.2 tools_4.1.1 gtable_0.3.0 glue_1.4.2 Rcpp_1.0.7
[36] DiceDesign_1.9 cellranger_1.1.0 vctrs_0.3.8 iterators_1.0.13 timeDate_3043.102 gower_0.2.2 xfun_0.25
[43] globals_0.14.0 rvest_1.0.1 lifecycle_1.0.0 future_1.22.1 MASS_7.3-54 ipred_0.9-11 vroom_1.5.4
[50] hms_1.1.0 parallel_4.1.1 RColorBrewer_1.1-2 yaml_2.2.1 curl_4.3.2 reticulate_1.20 sass_0.4.0
[57] rpart_4.1-15 reshape_0.8.8 stringi_1.7.4 tensorflow_2.6.0 foreach_1.5.1 checkmate_2.0.0 lhs_1.1.1
[64] hardhat_0.1.6 lava_1.6.10 repr_1.1.3 rlang_0.4.11 pkgconfig_2.0.3 lattice_0.20-44 labeling_0.4.2
[71] bit_4.0.4 tidyselect_1.1.1 parallelly_1.27.0 plyr_1.8.6 magrittr_2.0.1 R6_2.5.1 generics_0.1.0
[78] DBI_1.1.1 pillar_1.6.2 haven_2.4.3 whisker_0.4 withr_2.4.2 survival_3.2-11 nnet_7.3-16
[85] future.apply_1.8.1 modelr_0.1.8 crayon_1.4.1 utf8_1.2.2 tzdb_0.1.2 grid_4.1.1 readxl_1.3.1
[92] data.table_1.14.0 reprex_2.0.1 digest_0.6.27 GPfit_1.0-8 munsell_0.5.0
当我附加名为 tune 的包时，你问题中的第二个块工作正常。我认为通过 library(tidymodels) 包装器将 tidymodels 系列附加到您的工作区是一种更好的方法，而不是单独附加。
如果 tidymodels 包安装正确，（运行 a <- require(tidymodels) 和 a 应该合乎逻辑 TRUE）这段代码将起作用；
library(tidymodels)
set.seed(6735)
folds <- vfold_cv(mtcars, v = 5)
spline_rec <- recipe(mpg ~ ., data = mtcars) %>%
step_ns(disp) %>%
step_ns(wt)
lin_mod <- linear_reg() %>%
set_engine("lm")
control <- control_resamples(save_pred = TRUE)
spline_res <- fit_resamples(lin_mod, spline_rec, folds, control = control)