This is an helper object of type CVST.setup conatining all
necessary parameters for a CVST run.
constructCVSTModel(steps = 10, beta = 0.1, alpha = 0.01,
similaritySignificance = 0.05, earlyStoppingSignificance = 0.05,
earlyStoppingWindow = 3, regressionSimilarityViaOutliers = FALSE)Number of steps CVST should run
Significance level for H0.
Significance level for H1.
Significance level of the similarity test.
Significance level of the early stopping test.
Size of the early stopping window.
Should the less strict outlier-based similarity measure for regression tasks be used.
A CVST.setup object suitable for fastCV.
Tammo Krueger, Danny Panknin, and Mikio Braun. Fast cross-validation via sequential testing. Journal of Machine Learning Research 16 (2015) 1103-1155. URL https://jmlr.org/papers/volume16/krueger15a/krueger15a.pdf.