Add a Screener to a Learner

Usage

add_screener(learner, screener, screener_extra_args = NULL)

Arguments

learner: A learner to be modified by wrapping a screening stage on top of it.
screener: A screener to be added on top of the learner
screener_extra_args: Extra arguments to be passed to the screener

Value

A modified learner that when called on data and a formula now runs a screening stage before fitting the learner and returning a prediction function.

Examples

if (FALSE) { # \dontrun{

# construct a learner where variables with less than .6 correlation are screened out
lnr_glm_with_cor_60_thresholding <-
  add_screener(
    learner = lnr_glm,
    screener = screener_cor,
    screener_extra_args = list(threshold = .6)
  )

# train that on the mtcars dataset — also checking that extra arguments are properly passed to glm
lnr_glm_with_cor_60_thresholding(mtcars, formula = mpg ~ ., family = "gaussian")(mtcars)

# if we've screened out variables with low correlation to mpg, one such variable is qsec,
# so changing qsec shouldn't modify the predictions from our learned algorithm
mtcars_but_qsec_is_changed <- mtcars
mtcars_but_qsec_is_changed$qsec <- rnorm(n = nrow(mtcars))

identical(
  lnr_glm_with_cor_60_thresholding(mtcars, formula = mpg ~ .)(mtcars),
  lnr_glm_with_cor_60_thresholding(mtcars, formula = mpg ~ .)(mtcars_but_qsec_is_changed)
 )

# earth version
lnr_earth_with_cor_60_thresholding <-
  add_screener(
    learner = lnr_earth,
    screener = screener_cor,
    screener_extra_args = list(threshold = .6)
  )
lnr_earth_with_cor_60_thresholding(mtcars, formula = mpg ~ .)(mtcars)

identical(
  lnr_earth_with_cor_60_thresholding(mtcars, formula = mpg ~ .)(mtcars),
  lnr_earth_with_cor_60_thresholding(mtcars, formula = mpg ~ .)(mtcars)
 )

# note that this 'test' does not pass for a learner like randomForest that has
# some randomness in its predictions.

} # }