Create new task identical to the old one, but with newdata
instead
of old data. This should either preserve the orig.features
of the
original task, or should add new noise-features, in which case orig.features
should mark the features that correspond to the full original task.
clonetask(
task,
newdata,
newid,
orig.features = rep(TRUE, ncol(newdata) - length(getTaskTargetNames(task)))
)
Task
[Task]
mlr Task
to use.
[data.frame]
data to replace task
data with; must
include the target column with same name.
[character(1)]
ID to use for new Task
.
[logical]
features that correspond to original task's data.
Other Artificial Datasets:
create.hypersphere.data()
,
create.linear.data()
,
create.linear.toy.data()
,
create.regr.task()
,
task.add.permuted.cols()
,
task.add.random.cols()