mlr (version 2.17.0)

FailureModel: Failure model.

Description

A subclass of WrappedModel. It is created

• if you set the respective option in configureMlr - when a model internally crashed during training. The model always predicts NAs.

The if mlr option on.error.dump is TRUE, the FailureModel contains the debug trace of the error. It can be accessed with getFailureModelDump and inspected with debugger.

Its encapsulated learner.model is simply a string: The error message that was generated when the model crashed. The following code shows how to access the message.

See Also

Other debug: ResampleResult, getPredictionDump(), getRRDump()

Examples

# NOT RUN {
configureMlr(on.learner.error = "warn")
data = iris
data$newfeat = 1 # will make LDA crash
task = makeClassifTask(data = data, target = "Species")
m = train("classif.lda", task) # LDA crashed, but mlr catches this
print(m)
print(m$learner.model) # the error message
p = predict(m, task) # this will predict NAs
print(p)
print(performance(p))
configureMlr(on.learner.error = "stop")
# }