Code
new_rec <- recipe(~., data = circle_example) %>% step_upsample(class, ratio = 2)
Condition
Error:
! The `ratio` argument of `step_downsample()` was deprecated in themis 0.2.0 and is now defunct.
i Please use the `over_ratio` argument instead.
Code
rec %>% step_upsample(x) %>% prep()
Condition
Error in `step_upsample()`:
Caused by error in `prep()`:
! `x` should be a factor variable.
Code
rec %>% step_upsample(class, id) %>% prep()
Condition
Error in `step_upsample()`:
Caused by error in `prep()`:
! The selector should select at most a single variable.
Code
rec1_p
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 4
case_weights: 1
-- Training information
Training data contained 400 data points and no incomplete rows.
-- Operations
* Up-sampling based on: class | Trained, weighted
Code
rec1_p
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 4
case_weights: 1
-- Training information
Training data contained 400 data points and no incomplete rows.
-- Operations
* Up-sampling based on: class | Trained, ignored weights
Code
recipe(~., data = mtcars) %>% step_upsample(over_ratio = "yes") %>% prep()
Condition
Error in `step_upsample()`:
Caused by error in `prep()`:
! `over_ratio` must be a number, not the string "yes".
Code
recipe(~., data = mtcars) %>% step_upsample(seed = TRUE)
Condition
Error in `step_upsample()`:
! `seed` must be a whole number, not `TRUE`.
Code
bake(trained, new_data = circle_example[, -3])
Condition
Error in `step_upsample()`:
! The following required column is missing from `new_data`: class.
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Up-sampling based on: <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
* Up-sampling based on: <none> | Trained
Code
print(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 4
-- Operations
* Up-sampling based on: class
Code
prep(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 4
-- Training information
Training data contained 400 data points and no incomplete rows.
-- Operations
* Up-sampling based on: class | Trained
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