Parents (Total: 9)

The searched file hash is included in 9 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	86656
MD5	BBE948F08A28CE03B193E712C3DA8840
PackageDescription	GNU R 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.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-cvst
PackageSection	gnu-r
PackageVersion	0.2-2-3
SHA-1	7200E021540F70CF7C36199093C79518A6F6A76D
SHA-256	F6F03444889550BE4AECE08C1FFCC1120A79D7D1BA9AE2260E5329C267A6F330

Key	Value
FileSize	86904
MD5	D7766B97E27D7A8D3567C30FD4D3CD88
PackageDescription	GNU R 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-cvst
PackageSection	gnu-r
PackageVersion	0.2-2-3build1
SHA-1	FD45862F0D51425EA6008753BACB20978295BD62
SHA-256	BDE0F32A706FC5D0F0CFE0B7AF3FB3106BFAD4D588379211F3C2A0B5B78E55E1

Key	Value
FileSize	85952
MD5	A5E9E5CB6734D16B838DFBFF456BD0CE
PackageDescription	GNU R 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-cvst
PackageSection	gnu-r
PackageVersion	0.2-2-2
SHA-1	96EFBD09FF862B3EC1406941A3593CAF913FE855
SHA-256	13947E3FBAA0F01C8934720452910E003479DE98DCB674230D776770954988D1

Key	Value
MD5	3B4FF4E1584D374A1D5ABA8E6B3CE121
PackageArch	x86_64
PackageDescription	The 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.
PackageName	R-CVST
PackageRelease	2.24
PackageVersion	0.2.2
SHA-1	F61C4BBC76BFDE951A00350BB66FE1685887C361
SHA-256	083709A5528E2AB0A0039A4C1D4F4E54ABF4C5728ECBD6835B6ED54506C5A702

Key	Value
MD5	D00ED811A2D5223B90CF4FB97D1BB0CE
PackageArch	x86_64
PackageDescription	The 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.
PackageName	R-CVST
PackageRelease	lp153.2.3
PackageVersion	0.2.2
SHA-1	EE84C0AEF87804DA73D07E76C76301F4A3A43C15
SHA-256	746FFA0B518F011AB116100EF7303D50FB4DFBEE8308C2EBF06A1D6CC453CAB6

Key	Value
MD5	AE9C79468CD273777FCB82DDAEEE51F3
PackageArch	x86_64
PackageDescription	The 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.
PackageName	R-CVST
PackageRelease	lp152.2.6
PackageVersion	0.2.2
SHA-1	267F3C83EE5D8ADB2F413D8CF06C74B31EE72453
SHA-256	0EFFB06E84B4E5DBAC6D1E9174788933F67C38E779950BB0C30A43A811A9655D

Key	Value
MD5	0D408AA1A42074C62B0E0248EB361B38
PackageArch	x86_64
PackageDescription	The 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.
PackageName	R-CVST
PackageRelease	lp153.2.1
PackageVersion	0.2.2
SHA-1	1FCACE5685159988E209421EDBAAE82BB4023C25
SHA-256	A587FDA35E1907F69BF80556E80F2648440D013B5D4C122A05A016EFD519CAED

Key	Value
FileSize	85736
MD5	D4136FD7D7C78CBBBB5F1B26DE8F3E61
PackageDescription	GNU R 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.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-cvst
PackageSection	gnu-r
PackageVersion	0.2-2-2
SHA-1	411DAA051D0751653BF920FA8E1E3FA7C38FA918
SHA-256	E8C9921F645BA124EE65B55FF04F94395D0F22DFE8E0B47B75DA56A675C4EE9A

Key	Value
MD5	505A926DEEF0EE159CB61F00AB9BFE5B
PackageArch	x86_64
PackageDescription	The 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.
PackageMaintainer	https://www.suse.com/
PackageName	R-CVST
PackageRelease	lp154.2.1
PackageVersion	0.2.2
SHA-1	4FC0E11AFD02F976096882950C38A21E0F76B795
SHA-256	3194154DF768C67C120E5EEA066E6D53FA581015429CA2E70A1F1918FE1176B7