Parents (Total: 6)

The searched file hash is included in 6 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	27940
MD5	268710102DA484C90FEDC79863F2821A
PackageDescription	SVM trainer and classifier toolkit SVMs (Support Vector Machines) are supervised learning models with associated learning algorithms, and have been proven suitable for a large number of real-world applications, such as text categorization, hand-written character recognition, and image classification. TinySVM is an implementation specialising in pattern recognition. . This package provides tools for developing SVMs with TinySVM.
PackageMaintainer	Giulio Paci <giuliopaci@gmail.com>
PackageName	tinysvm
PackageSection	science
PackageVersion	0.09+dfsg-2
SHA-1	F83D90AC68AF2D69F985FB7E6564763C97ECB2D1
SHA-256	57E418AD95BE87680A1EC81A96DF89F9B64B39817FF67308B18EEB3B09554BD1

Key	Value
FileSize	27618
MD5	CD5303E5A9BA9584E6B0D84A881C127D
PackageDescription	SVM trainer and classifier toolkit SVMs (Support Vector Machines) are supervised learning models with associated learning algorithms, and have been proven suitable for a large number of real-world applications, such as text categorization, hand-written character recognition, and image classification. TinySVM is an implementation specialising in pattern recognition. . This package provides tools for developing SVMs with TinySVM.
PackageMaintainer	Giulio Paci <giuliopaci@gmail.com>
PackageName	tinysvm
PackageSection	science
PackageVersion	0.09+dfsg-2
SHA-1	724D322D3340CCAA25EACC9B614AC544850223E2
SHA-256	655361AE60510CBBE27C58A639CF0551DFF670BCDEFE60842682DCE3D9FC9E7C

Key	Value
FileSize	27906
MD5	BA5BA903FF9885F31004B4F25B3B2D14
PackageDescription	SVM trainer and classifier toolkit SVMs (Support Vector Machines) are supervised learning models with associated learning algorithms, and have been proven suitable for a large number of real-world applications, such as text categorization, hand-written character recognition, and image classification. TinySVM is an implementation specialising in pattern recognition. . This package provides tools for developing SVMs with TinySVM.
PackageMaintainer	Giulio Paci <giuliopaci@gmail.com>
PackageName	tinysvm
PackageSection	science
PackageVersion	0.09+dfsg-2
SHA-1	2B287A2720B553A1E282B8420B077FC183AD320D
SHA-256	ABD822F1EF9718D02153A91C9D229BA7EA23260B449FCAFE4099BB1E9DE2D533

Key	Value
FileSize	28360
MD5	8F842BEAFDAE492645C0312C76558E06
PackageDescription	SVM trainer and classifier toolkit SVMs (Support Vector Machines) are supervised learning models with associated learning algorithms, and have been proven suitable for a large number of real-world applications, such as text categorization, hand-written character recognition, and image classification. TinySVM is an implementation specialising in pattern recognition. . This package provides tools for developing SVMs with TinySVM.
PackageMaintainer	Giulio Paci <giuliopaci@gmail.com>
PackageName	tinysvm
PackageSection	science
PackageVersion	0.09+dfsg-2
SHA-1	2AF830E332FFEAD3662854B636B116792FED17D7
SHA-256	FE587A8B11EC58A1DA38BD9FCBB62B975922BC2D36159ECAF886C20D6ECCA3C4

Key	Value
FileSize	27980
MD5	97CB1BA1F4C7807F81D4FA5AB4C3A2E2
PackageDescription	SVM trainer and classifier toolkit SVMs (Support Vector Machines) are supervised learning models with associated learning algorithms, and have been proven suitable for a large number of real-world applications, such as text categorization, hand-written character recognition, and image classification. TinySVM is an implementation specialising in pattern recognition. . This package provides tools for developing SVMs with TinySVM.
PackageMaintainer	Giulio Paci <giuliopaci@gmail.com>
PackageName	tinysvm
PackageSection	science
PackageVersion	0.09+dfsg-2
SHA-1	922559E680CB271D12E4D1D86FF20E374FBA94F3
SHA-256	03352685C4EC39DD3378E57CA779708866EDE76105847BF0D55790435D20F527

Key	Value
FileSize	27780
MD5	C839194CF30C0270B52FA4FD737BA19D
PackageDescription	SVM trainer and classifier toolkit SVMs (Support Vector Machines) are supervised learning models with associated learning algorithms, and have been proven suitable for a large number of real-world applications, such as text categorization, hand-written character recognition, and image classification. TinySVM is an implementation specialising in pattern recognition. . This package provides tools for developing SVMs with TinySVM.
PackageMaintainer	Giulio Paci <giuliopaci@gmail.com>
PackageName	tinysvm
PackageSection	science
PackageVersion	0.09+dfsg-2
SHA-1	3186133DD82B26562A538D982228ED0E28879C75
SHA-256	474DEF0A9B87E816FD62ADE9332EDF03A4EBA1400A34EADA6B76D9ABC7E32009