Result for 6A28C12EDE589DF6C1BD4367CEFC16BCE6E4156C

Query result

Key Value
FileName./usr/lib64/R/library/CVST/Meta/package.rds
FileSize1058
MD5027C42BC5FCCB16E94CD958292FE5A44
SHA-16A28C12EDE589DF6C1BD4367CEFC16BCE6E4156C
SHA-256C18566F47778A537825F239779608738628B80DC772D7218FBF7EB77DF03F481
SSDEEP24:XEI6lCeLQ0Q/GCx3DMfn4699Ml96DPqdAdlsmWMmeh9hjW:XUCeLbQ/GQ3D2BMlmBdls8RjW
TLSHT13911B6F640CAA15C7DCD88C47208151607CF6ED24187DB12E4AC8D7ED0443A900C6AE5
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
MD5D00ED811A2D5223B90CF4FB97D1BB0CE
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
PackageReleaselp153.2.3
PackageVersion0.2.2
SHA-1EE84C0AEF87804DA73D07E76C76301F4A3A43C15
SHA-256746FFA0B518F011AB116100EF7303D50FB4DFBEE8308C2EBF06A1D6CC453CAB6