R: Setup for a CVST Run.

constructCVSTModel {CVST} | R Documentation

## 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 <tammokrueger@googlemail.com>

### References

Tammo Krueger, Danny Panknin, and Mikio Braun. Fast cross-validation via sequential testing. Journal of Machine Learning Research 16 (2015) 1103-1155. URL http://jmlr.org/papers/volume16/krueger15a/krueger15a.pdf.

### See Also

`fastCV`

[Package CVST version 0.2-2 Index]