Routes each row of newdata down the composite LORT by recursively
applying each node's cta_tree model via
cta_assign_endpoints.
Usage
# S3 method for class 'cta_ort'
predict(
object,
newdata,
type = c("class", "stratum", "path", "all"),
missing_action = c("na", "majority"),
...
)
Arguments
- object
A cta_ort from cta_fit(..., recursive = TRUE).
- newdata
Data frame or matrix matching the training X column layout.
- type
Character; one of "class" (default), "stratum",
"path", or "all".
- missing_action
Passed to each node-level
cta_assign_endpoints call. "na" (default):
observations with a missing split attribute return NA.
"majority": route to the majority-class child.
- ...
Unused.
Value
For type = "class": integer vector of predicted class labels
(length nrow(newdata)). For type = "stratum": integer
stratum_id vector. For type = "path": character path vector.
For type = "all": data.frame with columns
predicted_class, stratum_id, path,
prop_class1, stop_reason.
Note
predict.cta_ort is a legacy compatibility name; the class
cta_ort and all *.cta_ort methods refer to the implemented
LORT method. New docs and APIs should use LORT terminology.