shrink {hardhat} | R Documentation |
Subset only required columns
Description
shrink()
subsets data
to only contain the required columns specified by
the prototype, ptype
.
Usage
shrink(data, ptype)
Arguments
data |
A data frame containing the data to subset. |
ptype |
A data frame prototype containing the required columns. |
Details
shrink()
is called by forge()
before scream()
and before the actual
processing is done.
Value
A tibble containing the required columns.
Examples
# ---------------------------------------------------------------------------
# Setup
train <- iris[1:100, ]
test <- iris[101:150, ]
# ---------------------------------------------------------------------------
# shrink()
# mold() is run at model fit time
# and a formula preprocessing blueprint is recorded
x <- mold(log(Sepal.Width) ~ Species, train)
# Inside the result of mold() are the prototype tibbles
# for the predictors and the outcomes
ptype_pred <- x$blueprint$ptypes$predictors
ptype_out <- x$blueprint$ptypes$outcomes
# Pass the test data, along with a prototype, to
# shrink() to extract the prototype columns
shrink(test, ptype_pred)
# To extract the outcomes, just use the
# outcome prototype
shrink(test, ptype_out)
# shrink() makes sure that the columns
# required by `ptype` actually exist in the data
# and errors nicely when they don't
test2 <- subset(test, select = -Species)
try(shrink(test2, ptype_pred))
[Package hardhat version 1.4.0 Index]