makepredictcall.dw_transformer {datawizard} | R Documentation |
Utility Function for Safe Prediction with datawizard
transformers
Description
This 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.
Usage
## S3 method for class 'dw_transformer'
makepredictcall(var, call)
Arguments
var |
A variable. |
call |
The term in the formula, as a call. |
Value
A replacement for call
for the predvars
attribute of
the terms.
See Also
Examples
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)
[Package datawizard version 0.12.2 Index]