Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	411117AC6ECC5429E11FAA49882BFF39
PackageArch	x86_64
PackageDescription	Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
PackageName	R-regressoR
PackageRelease	lp152.1.1
PackageVersion	2.0.1
SHA-1	D790ADC3EA87C2A9CDFD80DB379564250E434E18
SHA-256	E821FED89F44020FDB9787A437A09BC348FF967DE1548D38DEB0642C81A63D53

Key	Value
MD5	66EB82D3D75EEE0D1F14992D9B28F860
PackageArch	x86_64
PackageDescription	Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
PackageName	R-regressoR
PackageRelease	lp153.1.1
PackageVersion	2.0.1
SHA-1	6EBF19B40D9944CF4F2D7965FF83C2561FE6C486
SHA-256	68EE6F69FA3B460CCA3BFE5D1CAC7817232A4EFA2BB3A146F31A13A4C67F4BE9

Key	Value
MD5	BD5F3932A816F45F639A2174E0C009CC
PackageArch	x86_64
PackageDescription	Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
PackageName	R-regressoR
PackageRelease	lp154.1.1
PackageVersion	2.0.1
SHA-1	EC52D06F3414F5B3FDE78A8E5AF2D1D79DA42538
SHA-256	ED116C9F7084BF73B41A95FD3B04EAD7AD4523C39DF2E811E9B6D1DF8EDDEA6C

Key	Value
MD5	270D6E8A4BA4F05751D40B83D6A91157
PackageArch	x86_64
PackageDescription	Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
PackageName	R-regressoR
PackageRelease	1.1
PackageVersion	2.0.1
SHA-1	F9AABAE08741D58DE75F397DAFA099CF5B84024F
SHA-256	7C71391E51893E5085007813EF2D8864A412A9AE215017530925EE5641A56899