makepredictcall.dw_transformer {datawizard} | R Documentation |
datawizard
transformersThis function allows for the use of (some of) datawizard
's transformers
inside a model formula. See examples below.
Currently, center()
, standardize()
, normalize()
, & rescale()
are
supported.
## S3 method for class 'dw_transformer' makepredictcall(var, call)
var |
A variable. |
call |
The term in the formula, as a call. |
A replacement for call
for the predvars
attribute of
the terms.
data("mtcars") train <- mtcars[1:30, ] test <- mtcars[31:32, ] m1 <- lm(mpg ~ center(hp), data = train) predict(m1, newdata = test) # Data is "centered" before the prediction is made, # according to the center of the old data m2 <- lm(mpg ~ standardize(hp), data = train) m3 <- lm(mpg ~ scale(hp), data = train) # same as above predict(m2, newdata = test) # Data is "standardized" before the prediction is made. predict(m3, newdata = test) # Data is "standardized" before the prediction is made. m4 <- lm(mpg ~ normalize(hp), data = mtcars) m5 <- lm(mpg ~ rescale(hp, to = c(-3, 3)), data = mtcars) (newdata <- data.frame(hp = c(range(mtcars$hp), 400))) # 400 is outside original range! model.frame(delete.response(terms(m4)), data = newdata) model.frame(delete.response(terms(m5)), data = newdata)