tests/testthat/_snaps/impute_lower.md

In tidymodels/recipes: Preprocessing and Feature Engineering Steps for Modeling

bad data

Code
  rec %>% step_impute_lower(carbon, hydrogen, has_neg) %>% prep()
Condition
  Error in `step_impute_lower()`:
  Caused by error in `prep()`:
  x The following columns negative values: has_neg.
  i Lower bound imputation is intended for data bounded at zero.

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

Code
  bake(imputed_trained, new_data = biomass[, 4:7])
Condition
  Error in `step_impute_lower()`:
  ! The following required column is missing from `new_data`: carbon.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Lower bound imputation 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 
  * Lower bound imputation for: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 3

  -- Operations 
  * Lower bound imputation for: carbon and hydrogen

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 3

  -- Training information 
  Training data contained 536 data points and no incomplete rows.

  -- Operations 
  * Lower bound imputation for: carbon and hydrogen | Trained

tidymodels/recipes documentation built on Oct. 3, 2024, 3:59 a.m.