generateThreshVsPerfData: Generate threshold vs. performance(s) for 2-class...
In riebetob/mlr: Machine Learning in R

Description Usage Arguments Value See Also

Generates data on threshold vs. performance(s) for 2-class classification that can be used for plotting.

1 2	generateThreshVsPerfData(obj, measures, gridsize = 100L, aggregate = TRUE, task.id = NULL)

`obj`	[(list of) `Prediction` \| (list of) `ResampleResult` \| `BenchmarkResult`] Single prediction object, list of them, single resample result, list of them, or a benchmark result. In case of a list probably produced by different learners you want to compare, then name the list with the names you want to see in the plots, probably learner shortnames or ids.
`measures`	[`Measure` \| list of `Measure`] Performance measure(s) to evaluate. Default is the default measure for the task, see here `getDefaultMeasure`.
`gridsize`	[`integer(1)`] Grid resolution for x-axis (threshold). Default is 100.
`aggregate`	[`logical(1)`] Whether to aggregate `ResamplePrediction`s or to plot the performance of each iteration separately. Default is `TRUE`.
`task.id`	[`character(1)`] Selected task in `BenchmarkResult` to do plots for, ignored otherwise. Default is first task.

[ThreshVsPerfData]. A named list containing the measured performance across the threshold grid, the measures, and whether the performance estimates were aggregated (only applicable for (list of) ResampleResults).

Other generate_plot_data: generateCalibrationData, generateCritDifferencesData, generateFeatureImportanceData, generateFilterValuesData, generateFunctionalANOVAData, generateLearningCurveData, generatePartialDependenceData, getFilterValues, plotFilterValues