create_ctree: Build all the conditional inference trees
In shapr: Prediction Explanation with Dependence-Aware Shapley Values

create_ctree

R Documentation

Build all the conditional inference trees

Build all the conditional inference trees

create_ctree(
  given_ind,
  x_train,
  mincriterion,
  minsplit,
  minbucket,
  use_partykit = "on_error"
)

`given_ind`	Integer vector. Indicates which features are conditioned on.
`x_train`	Data.table with training data.
`use_partykit`	String. In some semi-rare cases `partykit::ctree()` runs into an error related to the LINPACK used by R. To get around this problem, one may fall back to using the newer (but slower) `partykit::ctree()` function, which is a reimplementation of the same method. Setting this parameter to `"on_error"` (default) falls back to `partykit::ctree()`, if `party::ctree()` fails. Other options are `"never"`, which always uses `party::ctree()`, and `"always"`, which always uses `partykit::ctree()`. A warning message is created whenever `partykit::ctree()` is used.