classdist_shrunken.md
In recipes: Preprocessing and Feature Engineering Steps for Modeling

shrunken centroids

Code
  print(nsc_rec_half)
Message

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

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

  -- Operations 
  * Distance to shrunken centroids with: all_numeric_predictors()

Code
  print(nsc_rec_half_prep)
Message

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

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

  -- Training information 
  Training data contained 300 data points and no incomplete rows.

  -- Operations 
  * Distance to shrunken centroids with: x and y | Trained

Code
  print(tidy_spec)
Output
  # A tibble: 1 x 6
    terms                    value class type  threshold id                      
    <chr>                    <dbl> <chr> <chr>     <dbl> <chr>                   
  1 all_numeric_predictors()    NA <NA>  <NA>         NA classdist_shrunken_512IF

Code
  print(tidy_prep)
Output
  # A tibble: 18 x 6
     terms   value class type     threshold id                      
     <chr>   <dbl> <chr> <chr>        <dbl> <chr>                   
   1 x      2.70   a     global         0.5 classdist_shrunken_512IF
   2 x      8.11   a     by_class       0.5 classdist_shrunken_512IF
   3 x      1.37   a     shrunken       0.5 classdist_shrunken_512IF
   4 x      2.70   b     global         0.5 classdist_shrunken_512IF
   5 x     -0.0378 b     by_class       0.5 classdist_shrunken_512IF
   6 x     -0.0171 b     shrunken       0.5 classdist_shrunken_512IF
   7 x      2.70   c     global         0.5 classdist_shrunken_512IF
   8 x      0.0297 c     by_class       0.5 classdist_shrunken_512IF
   9 x      0      c     shrunken       0.5 classdist_shrunken_512IF
  10 y     -2.68   a     global         0.5 classdist_shrunken_512IF
  11 y      0.0516 a     by_class       0.5 classdist_shrunken_512IF
  12 y      0      a     shrunken       0.5 classdist_shrunken_512IF
  13 y     -2.68   b     global         0.5 classdist_shrunken_512IF
  14 y     -8.04   b     by_class       0.5 classdist_shrunken_512IF
  15 y     -1.24   b     shrunken       0.5 classdist_shrunken_512IF
  16 y     -2.68   c     global         0.5 classdist_shrunken_512IF
  17 y     -0.0445 c     by_class       0.5 classdist_shrunken_512IF
  18 y      0      c     shrunken       0.5 classdist_shrunken_512IF

Code
  recipe(class ~ x + y, data = nsc_test) %>% step_classdist_shrunken(
    all_numeric_predictors(), class = "class", threshold = -1) %>% prep()
Condition
  Error in `step_classdist_shrunken()`:
  Caused by error in `prep()`:
  ! `threshold` must be a number between 0 and 1, not the number -1.

Code
  recipe(class ~ x + y, data = nsc_test) %>% step_classdist_shrunken(
    all_numeric_predictors(), class = "class", sd_offset = -1) %>% prep()
Condition
  Error in `step_classdist_shrunken()`:
  Caused by error in `prep()`:
  ! `sd_offset` must be a number between 0 and 1, not the number -1.

empty printing

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

  -- Operations 
  * Distance to shrunken centroids with: <none>

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

  -- Training information 
  Training data contained 150 data points and no incomplete rows.

  -- Operations 
  * Distance to shrunken centroids with: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

  -- Operations 
  * Distance to shrunken centroids with: all_predictors()

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

  -- Training information 
  Training data contained 150 data points and no incomplete rows.

  -- Operations 
  * Distance to shrunken centroids with: Sepal.Length, ... | Trained