Elastic net error in R: "xFold01: preprocessor 1/1, model 1/10: Error: `y` should be one of the following classes: 'data.frame', 'matrix', 'factor'"

Hi, I'm new to machine learning so apologies if I'm just making a stupid mistake here: I'm trying to fit an elastic net model to some polling data from the UK in RStudio, using 10-fold cross validation. When I get to tuning the model, I get this error:

"x Fold01: preprocessor 1/1, model 1/10: Error: y should be one of the following classes: 'data.frame', 'matrix', 'factor'" for each fold/model.

I've got this exact code to work before, but for a different dataset. I've tried removing NA entries and various other cleaning methods. I've also tried converting variables to factors and specifying as.dataframe. Every time I get the same error.

I would be interested so see if anyone else has run into this before, or could advise me on it! I can't find much on it online.

I'm using several packages, mostly from the Tidyverse.

Here's my code for reference:

# Importing
bes <- read_dta("Data/BES2019_W20_v0.1-3.dta")
bes[bes==9999] <- NA
bes <- as.data.frame(bes)

# Splitting data
bes_split <- initial_split(bes, prop = 0.8)

bes_train <- training(bes_split)
bes_test <- testing(bes_split)

bes_folds <- vfold_cv(bes_train, v = 10)

# Recipe
elastic_recipe <-
    formula = turnoutUKGeneral ~ generalElectionVote,
    data = bes_train,
    na.rm = TRUE
  ) %>%
  step_zv(all_predictors()) %>% 
  step_normalize(all_predictors(), -all_nominal()) %>% 
  step_dummy(all_nominal()) %>% 

elastic_spec <-
  linear_reg(penalty = tune(), mixture = tune()) %>%
  set_mode("regression") %>%

elastic_workflow <-
  workflow() %>%
  add_recipe(elastic_recipe) %>%

# Tuning
elastic_grid <- grid_regular(
  penalty(range = c(-10, -2)),
  levels = c(10, 10)

elastic_tune <- elastic_workflow %>%
    resamples = bes_folds,
    grid = elastic_grid,

elastic_tune %>%

Session info:

R version 4.1.1 (2021-08-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22000)

Matrix products: default

[1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] glmnet_4.1-3        Matrix_1.3-4        vctrs_0.3.8         rlang_0.4.12        styler_1.6.2       
 [6] janitor_2.1.0       textrecipes_0.4.1   themis_0.1.4        rpart.plot_3.1.0    rpart_4.1-15       
[11] ranger_0.13.1       parttree_0.0.1.9000 gt_0.3.1            modelsummary_0.9.3  haven_2.4.3        
[16] patchwork_1.1.1     vip_0.3.2           gridExtra_2.3       jtools_2.1.4        tidytext_0.3.2     
[21] yardstick_0.0.8     workflowsets_0.1.0  workflows_0.2.4     tune_0.1.6          rsample_0.1.1      
[26] recipes_0.1.17      parsnip_0.1.7       modeldata_0.1.1     infer_1.0.0         dials_0.0.10       
[31] scales_1.1.1        broom_0.7.10        tidymodels_0.1.4    forcats_0.5.1       stringr_1.4.0      
[36] dplyr_1.0.7         purrr_0.3.4         readr_2.0.2         tidyr_1.1.4         tibble_3.1.5       
[41] ggplot2_3.3.5       tidyverse_1.3.1    

loaded via a namespace (and not attached):
 [1] readxl_1.3.1       mlr_2.19.0         backports_1.3.0    fastmatch_1.1-3    plyr_1.8.6         splines_4.1.1     
 [7] listenv_0.8.0      SnowballC_0.7.0    digest_0.6.28      foreach_1.5.1      htmltools_0.5.2    fansi_0.5.0       
[13] magrittr_2.0.1     checkmate_2.0.0    BBmisc_1.11        unbalanced_2.0     doParallel_1.0.16  tzdb_0.2.0        
[19] globals_0.14.0     modelr_0.1.8       gower_0.2.2        R.utils_2.11.0     hardhat_0.1.6      colorspace_2.0-2  
[25] rvest_1.0.2        xfun_0.27          crayon_1.4.2       jsonlite_1.7.2     survival_3.2-11    iterators_1.0.13  
[31] glue_1.4.2         gtable_0.3.0       ipred_0.9-12       R.cache_0.15.0     shape_1.4.6        future.apply_1.8.1
[37] DBI_1.1.1          Rcpp_1.0.7         GPfit_1.0-8        lava_1.6.10        prodlim_2019.11.13 httr_1.4.2        
[43] FNN_1.1.3          ellipsis_0.3.2     R.methodsS3_1.8.1  pkgconfig_2.0.3    ParamHelpers_1.14  nnet_7.3-16       
[49] dbplyr_2.1.1       utf8_1.2.2         tidyselect_1.1.1   DiceDesign_1.9     munsell_0.5.0      cellranger_1.1.0  
[55] tools_4.1.1        cli_3.1.0          generics_0.1.1     evaluate_0.14      fastmap_1.1.0      yaml_2.2.1        
[61] tables_0.9.6       knitr_1.36         fs_1.5.0           pander_0.6.4       RANN_2.6.1         future_1.23.0     
[67] R.oo_1.24.0        xml2_1.3.2         tokenizers_0.2.1   compiler_4.1.1     rstudioapi_0.13    reprex_2.0.1      
[73] lhs_1.1.3          stringi_1.7.5      lattice_0.20-44    pillar_1.6.4       lifecycle_1.0.1    furrr_0.2.3       
[79] data.table_1.14.2  R6_2.5.1           janeaustenr_0.1.5  parallelly_1.28.1  codetools_0.2-18   MASS_7.3-54       
[85] assertthat_0.2.1   ROSE_0.0-4         withr_2.4.2        parallel_4.1.1     hms_1.1.1          grid_4.1.1        
[91] timeDate_3043.102  class_7.3-19       rmarkdown_2.11     snakecase_0.11.0   parallelMap_1.5.1  pROC_1.18.0       
[97] lubridate_1.8.0   

Can you please provide a minimal reprex (reproducible example)? The goal of a reprex is to make it as easy as possible for me to recreate your problem so that I can fix it: please help me help you!

If you've never heard of a reprex before, start by reading "What is a reprex", and follow the advice further down that page.