Result for 68F8998B0113DDA777ADCE5CB86CC7EB4367F8B2

Query result

Key Value
FileName./usr/lib64/R/library/CVST/Meta/package.rds
FileSize1057
MD5E7F5E15BEB87F510442E519C4DBCE0A7
SHA-168F8998B0113DDA777ADCE5CB86CC7EB4367F8B2
SHA-2566A5D800B374F69A3D7BDE0BD4B52837F7E0A7DA70FF7A895274FA3542BE8234A
SSDEEP24:XODHjTUpSeQ0wUBTvvB4Zc9nZNNSLnjd9FNXxh/WH:XO7jTLKwEDB4Sj+zjd9v3m
TLSHT1E511B536242C1F1CFA0E3332B061A5129A4AB8ACD3848658CAF4C12DD0663BD44CA2AD
hashlookup:parent-total1
hashlookup:trust55

Network graph view

Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5AE9C79468CD273777FCB82DDAEEE51F3
PackageArchx86_64
PackageDescriptionThe fast cross-validation via sequential testing (CVST) procedure 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 under-performing 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.
PackageNameR-CVST
PackageReleaselp152.2.6
PackageVersion0.2.2
SHA-1267F3C83EE5D8ADB2F413D8CF06C74B31EE72453
SHA-2560EFFB06E84B4E5DBAC6D1E9174788933F67C38E779950BB0C30A43A811A9655D