generateOverfitAnalysis: Generates Data for Overfitting Analysis

In jakob-r/mlrOverfit: Detect and Visualize Overfitting Effects

Description

Generates all necessary data to perform the overfitting analysis

Usage

generateOverfitAnalysis(
  task,
  learner,
  tune.control = NULL,
  par.set,
  learner.tuned = NULL,
  only.on.improvement = FALSE,
  outer.resampling = cv10,
  ...
)

Arguments

task	[Task]
learner	[Learner] Learner to be tuned and analyzed.
tune.control	[TuneControl] If none is supplied a random search with 10 iterations will be performed.
par.set	[ParamSet]
learner.tuned	[Learner] Learner wrapped with [makeTuneWrapper]
only.on.improvement	[logical(1)] Calculating the performances can be epensive. Do you just want to calculate them, when a new good performance is detected in the inner performance? Default is FALSE.
outer.resampling	[ResampleDesc | ResampleInstance] Default is 10CV.
...	[...] Arguments passed to resampleOverfit

jakob-r/mlrOverfit documentation built on July 4, 2020, 2:06 a.m.