rose.md
In themis: Extra Recipes Steps for Dealing with Unbalanced Data

bad data

Code
  rec %>% step_rose(x) %>% prep()
Error <recipes_error_step>
  Error in `step_rose()`:
  Caused by error in `prep()`:
  ! `x` should be a factor variable.

Code
  rec %>% step_rose(class, id) %>% prep()
Error <recipes_error_step>
  Error in `step_rose()`:
  Caused by error in `prep()`:
  ! The selector should select at most a single variable

NA in response

Code
  recipe(Status ~ Age, data = credit_data0) %>% step_rose(Status) %>% prep()
Error <recipes_error_step>
  Error in `step_rose()`:
  Caused by error in `prep()`:
  ! Cannot have any missing values. NAs found ind: Status.

only except 2 classes

Code
  recipe(~., data = df_char) %>% step_rose(x) %>% prep()
Error <recipes_error_step>
  Error in `step_rose()`:
  Caused by error in `prep()`:
  ! `x` must only have 2 levels.

empty printing

Code
  rec
Message <cliMessage>

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Operations 
  * ROSE based on: <none>

Code
  rec
Message <cliMessage>

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Training information 
  Training data contained 32 data points and no incomplete rows.

  -- Operations 
  * ROSE based on: <none> | Trained

printing

Code
  print(rec)
Message <cliMessage>

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 2

  -- Operations 
  * ROSE based on: class

Code
  prep(rec)
Message <cliMessage>

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 2

  -- Training information 
  Training data contained 400 data points and no incomplete rows.

  -- Operations 
  * ROSE based on: class | Trained