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.
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 × 1
#> .outcome
#> <int>
#> 1 1
#> 2 2
#> 3 3
#> 4 4
#> 5 5
standardize(factor(letters[1:5]))
#> # A tibble: 5 × 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 × 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 × 2
#> x y
#> <int> <int>
#> 1 1 6
#> 2 2 7
#> 3 3 8
#> 4 4 9
#> 5 5 10