tests/testthat/_snaps/smoten.md

In themis: Extra Recipes Steps for Dealing with Unbalanced Data

errors if there isn't enough data

Code
  prep(step_smoten(recipe(class ~ x, data = df), class, neighbors = 5))
Condition
  Error in `step_smoten()`:
  Caused by error in `bake()`:
  ! The minority class "min" does not have enough observations to perform SMOTEN.
  i 3 observations were found, but 6 are needed.

errors on numeric predictors

Code
  prep(step_smoten(recipe(class ~ x, data = df), class))
Condition
  Error in `step_smoten()`:
  Caused by error in `prep()`:
  ! All predictor columns for this function should be categorical (factor or character).  Non-categorical column found: `x`.

bad data

Code
  prep(step_smoten(recipe(~., data = df), class, id))
Condition
  Error in `step_smoten()`:
  Caused by error in `prep()`:
  ! The selector should select at most a single variable.

NA in response

Code
  prep(step_smoten(recipe(class ~ x + y, data = df), class))
Condition
  Error in `step_smoten()`:
  Caused by error in `prep()`:
  ! Cannot have any missing values. NAs found in x.

indicator_column bad args

Code
  step_smoten(recipe(class ~ x + y, data = cat_example), class, indicator_column = 1)
Condition
  Error in `step_smoten()`:
  ! `indicator_column` must be a single string or `NULL`, not the number 1.

Code
  prep(step_smoten(recipe(class ~ x + y, data = cat_example), class,
  indicator_column = ""))
Condition
  Error in `step_smoten()`:
  ! `indicator_column` must be a single string or `NULL`, not the empty string "".

Code
  prep(step_smoten(recipe(class ~ x + y, data = cat_example), class,
  indicator_column = "x"))
Condition
  Error in `step_smoten()`:
  Caused by error in `prep()`:
  ! Name collision occurred. The following variable names already exist:
  * `x`

bad args

Code
  prep(step_smoten(recipe(class ~ x + y, data = cat_example), over_ratio = "yes"))
Condition
  Error in `step_smoten()`:
  Caused by error in `prep()`:
  ! `over_ratio` must be a number, not the string "yes".

Code
  prep(step_smoten(recipe(class ~ x + y, data = cat_example), neighbors = TRUE))
Condition
  Error in `step_smoten()`:
  Caused by error in `prep()`:
  ! `neighbors` must be a whole number, not `TRUE`.

Code
  step_smoten(recipe(class ~ x + y, data = cat_example), seed = TRUE)
Condition
  Error in `step_smoten()`:
  ! `seed` must be a whole number, not `TRUE`.

unused outcome levels are skipped with a warning (#238)

Code
  res <- bake(prep(step_smoten(recipe(class ~ x + y, data = cat_example), class)),
  new_data = NULL)
Condition
  Warning in `prep()`:
  Unused factor level "unused" in `class` was dropped.
  i  Level with zero observations is skipped when computing sampling targets.

step_smoten() checks over_ratio names when prepped (#323)

Code
  prep(step_smoten(recipe(class ~ ., data = df), class, over_ratio = c(a = 1,
    potato = 1)))
Condition
  Error in `step_smoten()`:
  Caused by error in `prep()`:
  ! `over_ratio` names must be levels of the outcome.
  x Unknown name: "potato".
  i Available levels: "a", "b", and "c".

bake method errors when needed non-standard role columns are missing

Code
  bake(trained, new_data = cat_example[, -3])
Condition
  Error in `step_smoten()`:
  ! The following required column is missing from `new_data`: class.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * SMOTEN based on: <none>

Code
  rec
Message

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

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

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

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

printing

Code
  print(rec)
Message

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

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

  -- Operations 
  * SMOTEN based on: class

Code
  prep(rec)
Message

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

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

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

  -- Operations 
  * SMOTEN based on: class | Trained

themis documentation built on Aug. 2, 2026, 9:07 a.m.