Measure performance of prediction.
Measures the quality of a prediction w.r.t. some performance measure.
performance(pred, measures, task = NULL, model = NULL, feats = NULL)
Prediction] Prediction object.
Measure| list of
Measure] Performance measure(s) to evaluate. Default is the default measure for the task, see here
Task] Learning task, might be requested by performance measure, usually not needed except for clustering.
WrappedModel] Model built on training data, might be requested by performance measure, usually not needed.
data.frame] Features of predicted data, usually not needed except for clustering. If the prediction was generated from a
task, you can also pass this instead and the features are extracted from it.
numeric]. Performance value(s), named by measure(s).
training.set = seq(1, nrow(iris), by = 2) test.set = seq(2, nrow(iris), by = 2) task = makeClassifTask(data = iris, target = "Species") lrn = makeLearner("classif.lda") mod = train(lrn, task, subset = training.set) pred = predict(mod, newdata = iris[test.set, ]) performance(pred, measures = mmce) # Compute multiple performance measures at once ms = list("mmce" = mmce, "acc" = acc, "timetrain" = timetrain) performance(pred, measures = ms, task, mod)
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