CVST: Fast Cross-Validation via Sequential Testing
This package implements the fast cross-validation via
sequential testing (CVST) procedure. CVST is an improved
cross-validation procedure which uses non-parametric testing
coupled with sequential analysis to determine the best
parameter set on linearly increasing subsets of the data. By
eliminating underperforming candidates quickly and keeping
promising candidates as long as possible, the method speeds up
the computation while preserving the capability of a full
cross-validation. Additionally to the CVST the package contains
an implementation of the ordinary k-fold cross-validation with
a flexible and powerful set of helper objects and methods to
handle the overall model selection process. The implementations
of the Cochran's Q test with permutations and the sequential
testing framework of Wald are generic and can therefore also be
used in other contexts.
| Version: |
0.2 |
| Depends: |
kernlab, Matrix |
| Published: |
2013-04-16 |
| Author: |
Tammo Krueger, Mikio Braun |
| Maintainer: |
Tammo Krueger <tammokrueger at googlemail.com> |
| License: |
GPL (≥ 2.0) |
| NeedsCompilation: |
no |
| CRAN checks: |
CVST results |
Downloads: