A resample result is created by resample and contains the following object members:
character(1)):Name of the Task.
character(1)):Name of the Learner.
Gives you access to performance measurements on the individual test sets. Rows correspond to sets in resampling iterations, columns to performance measures.
Gives you access to performance measurements on the individual training sets. Rows correspond to sets in resampling iterations, columns to performance measures. Usually not available, only if specifically requested, see general description above.
Named vector of aggregated performance values. Names are coded like this <measure>.<aggregation>.
Number of rows equals resampling iterations and columns are: “iter”, “train”, “predict”. Stores error messages generated during train or predict, if these were caught via configureMlr.
List with length equal to number of resampling iterations. Contains lists
of dump.frames objects that can be fed to debugger() to inspect
error dumps generated on learner errors. One iteration can generate more than
one error dump depending on which of training, prediction on training set,
or prediction on test set, operations fail. Therefore the lists have named
slots $train, $predict.train, or $predict.test if relevant.
The error dumps are only saved when option on.error.dump is TRUE.
Container for all predictions during resampling.
List of fitted models or NULL.
List of extracted parts from fitted models or NULL.
numeric(1)):Time in seconds it took to execute the resampling.
The print method of this object gives a short overview, including task and learner ids, aggregated measures and runtime for the resampling.
Other resample: ResamplePrediction,
addRRMeasure,
getRRPredictionList,
getRRPredictions,
getRRTaskDescription,
getRRTaskDesc,
makeResampleDesc,
makeResampleInstance,
resample
Other debug: FailureModel,
getPredictionDump, getRRDump