Result for 7FFD3A983EBB36FB9ACF60BB9D48AA6B5E10E5B8

Query result

Key Value
FileName./usr/lib64/R/library/CVST/DESCRIPTION
FileSize1272
MD5FBE8D34B53ADFF7AE4FC17D9B23551A2
SHA-17FFD3A983EBB36FB9ACF60BB9D48AA6B5E10E5B8
SHA-256930F18922B5349CB7FD2B54268C687167E524CA045B23ED6CBDB1CDA9B7017BB
SSDEEP24:8aBXK4PaCUrfWlB2C+yph+wCAtjmoqmFzkkzpkkew1n4Hpr7FDCZ:3hK4PYrulB2C+yph+w3tjmKlkfkewR4M
TLSHT17321724260C92321779B02BF13EB43D6272882057BFAC05C815AC4160745CF227B37FC
hashlookup:parent-total1
hashlookup:trust55

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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
MD50D408AA1A42074C62B0E0248EB361B38
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
PackageReleaselp153.2.1
PackageVersion0.2.2
SHA-11FCACE5685159988E209421EDBAAE82BB4023C25
SHA-256A587FDA35E1907F69BF80556E80F2648440D013B5D4C122A05A016EFD519CAED