score.apd_pca {applicable}  R Documentation 
apd_pca
Predict from a apd_pca
## S3 method for class 'apd_pca' score(object, new_data, type = "numeric", ...)
object 
A 
new_data 
A data frame or matrix of new samples. 
type 
A single character. The type of predictions to generate. Valid options are:

... 
Not used, but required for extensibility. 
The function computes the principal components of the new data and
their percentiles as compared to the training data. The number of principal
components computed depends on the threshold
given at fit time. It also
computes the multivariate distance between each principal component and its
mean.
A tibble of predictions. The number of rows in the tibble is guaranteed
to be the same as the number of rows in new_data
.
train < mtcars[1:20,] test < mtcars[21:32, 1] # Fit mod < apd_pca(mpg ~ cyl + log(drat), train) # Predict, with preprocessing score(mod, test)