Code
te_1 <- bake(rec_1, sacr_te)
Condition
Warning:
! There are new levels in `city`: "WEST_SACRAMENTO".
i Consider using step_novel() (`?recipes::step_novel()`) before `step_unknown()` to handle unseen values.
* New levels will be coerced to `NA` by `step_unknown()`.
Warning:
! There are new levels in `zip`: "z95691".
i Consider using step_novel() (`?recipes::step_novel()`) before `step_unknown()` to handle unseen values.
* New levels will be coerced to `NA` by `step_unknown()`.
Code
recipe(~., data = sacr_tr) %>% step_unknown(sqft) %>% prep()
Condition
Error in `step_unknown()`:
Caused by error in `prep()`:
x All columns selected for the step should be string, factor, or ordered.
* 1 integer variable found: `sqft`
Code
recipe(~., data = sacr_tr) %>% step_unknown(city, new_level = "FAIR_OAKS") %>%
prep()
Condition
Error in `step_unknown()`:
Caused by error in `prep()`:
! Columns already contain the level "FAIR_OAKS": city.
Code
recipe(~., data = sacr_tr) %>% step_unknown(city, new_level = 2) %>% prep()
Condition
Error in `step_unknown()`:
Caused by error in `prep()`:
! `new_level` must be a single string, not the number 2.
Code
bake(rec_1, sacr_te[3:ncol(sacr_te)])
Condition
Error in `step_unknown()`:
! The following required columns are missing from `new_data`: city and zip.
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Unknown factor level assignment 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
* Unknown factor level assignment for: <none> | Trained
Code
print(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 9
-- Operations
* Unknown factor level assignment for: city and zip
Code
prep(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 9
-- Training information
Training data contained 800 data points and no incomplete rows.
-- Operations
* Unknown factor level assignment for: city and zip | Trained
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