Condition classes for mlr3.
Usage
error_config(msg, ..., class = NULL, signal = TRUE)
error_input(msg, ..., class = NULL, signal = TRUE)
error_timeout(signal = TRUE)
error_mlr3(msg, ..., class = NULL, signal = TRUE)
warning_mlr3(msg, ..., class = NULL, signal = TRUE)
warning_config(msg, ..., class = NULL, signal = TRUE)
warning_input(msg, ..., class = NULL, signal = TRUE)
error_learner(msg, ..., class = NULL, signal = TRUE)
error_learner_train(msg, ..., class = NULL, signal = TRUE)
error_learner_predict(msg, ..., class = NULL, signal = TRUE)
Arguments
- msg
(
character(1)
)
Error message.- ...
(any)
Passed tosprintf()
.- class
(
character
)
Additional class(es).- signal
(
logical(1)
)
IfTRUE
, the condition object is returned.
Formatting
It is also possible to use formatting options as defined in cli::cli_bullets
.
Errors
error_mlr3()
for the baseMlr3Error
class.error_config()
for theMlr3ErrorConfig
class, which signals that a user has misconfigured something (e.g. invalid learner configuration).error_input()
for theMlr3ErrorInput
if an invalid input was provided. method.error_timeout()
for theMlr3ErrorTimeout
, signalling a timeout (encapsulation).error_learner()
for theMlr3ErrorLearner
, signalling a learner error.error_learner_train()
for theMlr3ErrorLearner
, signalling a learner training error.error_learner_predict()
for theMlr3ErrorLearner
, signalling a learner prediction error.