constructCVSTModel: Setup for a CVST Run.

In CVST: Fast Cross-Validation via Sequential Testing

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

CVST documentation built on March 18, 2022, 5:59 p.m.