I am using
tidymodels to explore the
small_fine_foods dataset where I'm just trying to replicate the analysis done in this blog post. It seems to be something small but the models all fail with:
Error: Columns (
review) are not numeric; cannot convert to matrix
Below is a minimal example. Can anyone see where my error is?
library(recipes) library(modeldata) library(textrecipes) data("small_fine_foods") training_data library(hardhat) sparse_bp <- default_recipe_blueprint(composition = "dgCMatrix") text_rec <- recipe(score ~ review, data = training_data) %>% step_tokenize(review) lasso_spec <- logistic_reg(penalty = 0.02, mixture = 1) %>% set_engine("glmnet") wf_sparse <- workflow() %>% add_recipe(text_rec, blueprint = sparse_bp) %>% add_model(lasso_spec) food_folds <- vfold_cv(training_data, strata = score) sparse = fit_resamples(wf_sparse, food_folds) # Error: Columns (`review`) are not numeric; cannot convert to matrix # The tokens appear to be present text_rec %>% prep() %>% bake(new_data = NULL) # # A tibble: 4,000 x 2 # review score # <tknlist> <fct> # 1 [13 tokens] other # 2 [94 tokens] great # 3 [104 tokens] great # 4 [36 tokens] great # 5 [19 tokens] great # 6 [27 tokens] great # 7 [83 tokens] other # 8 [53 tokens] great # 9 [55 tokens] great # 10 [45 tokens] great # # ... with 3,990 more rows