R: Measure performance of prediction.

performance {mlr} | R Documentation

## Measure performance of prediction.

### Description

Measures the quality of a prediction w.r.t. some performance measure.

### Usage

    performance(
      pred,
      measures,
      task = NULL,
      model = NULL,
      feats = NULL,
      simpleaggr = FALSE
    )

### Arguments

`pred` | (Prediction) Prediction object.
`measures` | (Measure | list of Measure) Performance measure(s) to evaluate. Default is the default measure for the task, see here getDefaultMeasure.
`task` | (Task) Learning task, might be requested by performance measure, usually not needed except for clustering or survival.
`model` | (WrappedModel) Model built on training data, might be requested by performance measure, usually not needed except for survival.
`feats` | (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.
`simpleaggr` | (logical) If TRUE, aggregation of `ResamplePrediction` objects is skipped. This is used internally for threshold tuning. Default is `FALSE`.

### Value

(named numeric). Performance value(s), named by measure(s).

### See Also

Other performance: `ConfusionMatrix`, `calculateConfusionMatrix()`, `calculateROCMeasures()`, `estimateRelativeOverfitting()`, `makeCostMeasure()`, `makeCustomResampledMeasure()`, `makeMeasure()`, `measures`, `setAggregation()`, `setMeasurePars()`

### Examples

    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)

[Package mlr version 2.19.0 Index]