constructCVSTModel {CVST}

Setup for a CVST Run.

Description

This is an helper object of type CVST.setup conatining all necessary parameters for a CVST run.

Usage

constructCVSTModel(steps = 10, beta = 0.1, alpha = 0.01,
similaritySignificance = 0.05, earlyStoppingSignificance = 0.05,
earlyStoppingWindow = 3, regressionSimilarityViaOutliers = FALSE)

Arguments

steps

Number of steps CVST should run

beta

Significance level for H0.

alpha

Significance level for H1.

similaritySignificance

Significance level of the similarity test.

earlyStoppingSignificance

Significance level of the early stopping test.

earlyStoppingWindow

Size of the early stopping window.

regressionSimilarityViaOutliers

Should the less strict outlier-based similarity measure for regression tasks be used.

Value

A CVST.setup object suitable for fastCV.

Author(s)

Tammo Krueger <[e-mail]>

References

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.

See Also

fastCV