Code
new_values_ch <- bake(class_test, new_data = new_dat_ch, contains("embed"))
Condition
Warning:
! There was 1 column that was a factor when the recipe was prepped:
* `x3`
i This may cause errors when processing new data.
Code
new_values_ch <- bake(class_test, new_data = new_dat_ch, contains("embed"))
Condition
Warning:
! There was 1 column that was a factor when the recipe was prepped:
* `x3`
i This may cause errors when processing new data.
Code
recipe(Species ~ ., data = three_class) %>% step_embed(Sepal.Length, outcome = vars(
Species)) %>% prep(training = three_class, retain = TRUE)
Condition
Error in `step_embed()`:
Caused by error in `prep()`:
x All columns selected for the step should be string, factor, or ordered.
* 1 double variable found: `Sepal.Length`
Code
prep(rec, training = dat)
Condition
Error in `step_embed()`:
Caused by error in `bake()`:
! Name collision occurred. The following variable names already exist:
* `x3_embed_1`
Code
bake(rec_trained, new_data = ex_dat[, -3])
Condition
Error in `step_embed()`:
! The following required column is missing from `new_data`: x3.
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Embedding of factors via tensorflow for: <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
* Embedding of factors via tensorflow for: <none> | Trained
Code
rec <- prep(rec)
Condition
Warning:
`keep_original_cols` was added to `step_embed()` after this recipe was created.
i Regenerate your recipe to avoid this warning.
Code
print(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 3
-- Operations
* Embedding of factors via tensorflow for: x3
Code
prep(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 3
-- Training information
Training data contained 500 data points and no incomplete rows.
-- Operations
* Embedding of factors via tensorflow for: x3 | Trained
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