Most of the time, the input to a model should be flexible enough to capture a number of different input types from the user. standardize() focuses on capturing the flexibility in the outcome.

standardize(y)

Arguments

y

The outcome. This can be:

  • A factor vector

  • A numeric vector

  • A 1D numeric array

  • A numeric matrix with column names

  • A 2D numeric array with column names

  • A data frame with numeric or factor columns

Value

All possible values of y are transformed into a tibble for standardization. Vectors are transformed into a tibble with a single column named ".outcome".

Details

standardize() is called from mold() when using an XY interface (i.e. a y argument was supplied).

Examples

standardize(1:5)
#> # A tibble: 5 x 1 #> .outcome #> <int> #> 1 1 #> 2 2 #> 3 3 #> 4 4 #> 5 5
standardize(factor(letters[1:5]))
#> # A tibble: 5 x 1 #> .outcome #> <fct> #> 1 a #> 2 b #> 3 c #> 4 d #> 5 e
mat <- matrix(1:10, ncol = 2) colnames(mat) <- c("a", "b") standardize(mat)
#> # A tibble: 5 x 2 #> a b #> <int> <int> #> 1 1 6 #> 2 2 7 #> 3 3 8 #> 4 4 9 #> 5 5 10
df <- data.frame(x = 1:5, y = 6:10) standardize(df)
#> # A tibble: 5 x 2 #> x y #> <int> <int> #> 1 1 6 #> 2 2 7 #> 3 3 8 #> 4 4 9 #> 5 5 10