Code
prep(rec, training = dat)
Condition
Error in `step_tfidf()`:
Caused by error in `bake()`:
! Name collision occurred. The following variable names already exist:
* `tfidf_text_i`
Code
expect_equal(slice(bake(rec, data), 1), tibble(tfidf_text_g = log(1 + 2 / 1) /
2, tfidf_text_i = log(1 + 2 / 2) / 2))
Condition
Warning:
Please retrain this recipe with version 0.5.1 or higher.
i A data leakage bug has been fixed for `step_tfidf()`.
Code
expect_equal(bake(rec, slice(data, 1)), tibble(tfidf_text_g = log(1 + 2 / 2) /
2, tfidf_text_i = log(1 + 2 / 2) / 2))
Condition
Warning:
Please retrain this recipe with version 0.5.1 or higher.
i A data leakage bug has been fixed for `step_tfidf()`.
Code
prep(step_tfidf(recipe(~., data = mtcars), vocabulary = 1:10))
Condition
Error in `step_tfidf()`:
Caused by error in `prep()`:
! `vocabulary` must be a character vector or `NULL`, not an integer vector.
Code
prep(step_tfidf(recipe(~., data = mtcars), smooth_idf = "yes"))
Condition
Error in `step_tfidf()`:
Caused by error in `prep()`:
! `smooth_idf` must be `TRUE` or `FALSE`, not the string "yes".
Code
prep(step_tfidf(recipe(~., data = mtcars), norm = "yes"))
Condition
Error in `step_tfidf()`:
Caused by error in `prep()`:
! `norm` must be one of "l1", "l2", or "none", not "yes".
Code
prep(step_tfidf(recipe(~., data = mtcars), sublinear_tf = "yes"))
Condition
Error in `step_tfidf()`:
Caused by error in `prep()`:
! `sublinear_tf` must be `TRUE` or `FALSE`, not the string "yes".
Code
prep(step_tfidf(recipe(~., data = mtcars), prefix = NULL))
Condition
Error in `step_tfidf()`:
Caused by error in `prep()`:
! `prefix` must be a single string, not `NULL`.
Code
bake(trained, new_data = tokenized_test_data[, -1])
Condition
Error in `step_tfidf()`:
! The following required column is missing from `new_data`: text.
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Term frequency-inverse document frequency with: <none>
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Training information
Training data contained 32 data points and no incomplete rows.
-- Operations
* Term frequency-inverse document frequency with: <none> | Trained
Code
rec <- prep(rec)
Condition
Warning:
`keep_original_cols` was added to `step_tfidf()` after this recipe was created.
i Regenerate your recipe to avoid this warning.
Code
print(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 1
-- Operations
* Tokenization for: text
* Term frequency-inverse document frequency with: text
Code
prep(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 1
-- Training information
Training data contained 4 data points and no incomplete rows.
-- Operations
* Tokenization for: text | Trained
* Term frequency-inverse document frequency with: text | Trained
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.