tests/testthat/_snaps/relu.md

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

input checking

Code
  recipe(~., data = df) %>% step_relu(val1, shift = TRUE) %>% prep(df, verbose = FALSE)
Condition
  Error in `step_relu()`:
  Caused by error in `prep()`:
  ! `shift` must be a number, not `TRUE`.

Code
  recipe(~., data = df) %>% step_relu(val1, reverse = 3) %>% prep(df, verbose = FALSE)
Condition
  Error in `step_relu()`:
  Caused by error in `prep()`:
  ! `reverse` must be `TRUE` or `FALSE`, not the number 3.

Code
  recipe(~., data = df) %>% step_relu(val1, smooth = "cat") %>% prep(df, verbose = FALSE)
Condition
  Error in `step_relu()`:
  Caused by error in `prep()`:
  ! `smooth` must be `TRUE` or `FALSE`, not the string "cat".

Code
  recipe(~., data = df) %>% step_relu(val2) %>% prep(df, verbose = FALSE)
Condition
  Error in `step_relu()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 factor variable found: `val2`

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

Code
  bake(rec, df[, 2, drop = FALSE])
Condition
  Error in `step_relu()`:
  ! The following required column is missing from `new_data`: val1.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Adding relu transform 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 
  * Adding relu transform for: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 11

  -- Operations 
  * Adding relu transform for: disp

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 11

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

  -- Operations 
  * Adding relu transform for: disp | Trained

tidymodels/recipes documentation built on Jan. 25, 2025, 7:30 a.m.