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.
Other debug: ResampleResult
,
getPredictionDump
, getRRDump
1 2 3 4 5 6 7 8 9 10 11 | 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")
|
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