Parents (Total: 36)

The searched file hash is included in 36 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	FB0FDC148881D2057ED6FD3B3B86138D
PackageArch	noarch
PackageDescription	Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainer	Fedora Project
PackageName	weka
PackageRelease	1.fc18
PackageVersion	3.6.8
SHA-1	0B8CB68B514D3C4025099E0DB6A462AAED99D026
SHA-256	3D35131B632B13C0EEE5EE12D6A525DE6C4F90FEF6ED1F3839056C2AA131FB6A

Key	Value
MD5	6CA942E1743D91DED4B1BFD08D9AF700
PackageArch	x86_64
PackageDescription	An R interface to Weka (Version 3.7.10). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars. For more information on Weka see <http://www.cs.waikato.ac.nz/~ml/weka/>.
PackageName	R-RWeka
PackageRelease	1.123
PackageVersion	0.4.39
SHA-1	0E40454308D759B3F7D76AC6CA2EE8C7B9BE7D65
SHA-256	DD04AF53C3BA3674FEC64E770440628FD9F92B9E062972FDF719109A60E0167A

Key	Value
MD5	26BC7C70CBB10CC5B371354932D201BA
PackageArch	x86_64
PackageDescription	An R interface to Weka (Version 3.7.10). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars. For more information on Weka see <http://www.cs.waikato.ac.nz/~ml/weka/>.
PackageName	R-RWeka
PackageRelease	1.14
PackageVersion	0.4.39
SHA-1	200251EF4DF12DC8E8A4ED2D0B62AA914777F89E
SHA-256	F638E265C4C7F06E3F5FFC874B2D359977109BC2FC2510E031892828C5C27096

Key	Value
MD5	F682D20D190BC1A32EE58A4D1E90DCA9
PackageArch	x86_64
PackageDescription	An R interface to Weka (Version 3.7.10). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars. For more information on Weka see <http://www.cs.waikato.ac.nz/~ml/weka/>.
PackageName	R-RWeka
PackageRelease	lp151.1.58
PackageVersion	0.4.39
SHA-1	222C4EADFBCFCE6387D5FE33A3D3EA2DAAD80639
SHA-256	09DB681F992626D0F6764B66D264E3AE03692E9E910604B81D4CFFF04990C435

Key	Value
MD5	5EA8EB2849C90A6BDD85FC2DF0DA2A87
PackageArch	i586
PackageDescription	An R interface to Weka (Version 3.7.10). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars. For more information on Weka see <http://www.cs.waikato.ac.nz/~ml/weka/>.
PackageName	R-RWeka
PackageRelease	1.93
PackageVersion	0.4.39
SHA-1	3154BF2E77CA73DF6CDA29FA429B2E206CA03B51
SHA-256	27D1DA71A1D553BF5D66C4E006B817B8A7ACF516B4F5A5FDCF60F49374EE8D69

Key	Value
MD5	3E729A70F089D3A2D172340F3C5596CE
PackageArch	noarch
PackageDescription	Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainer	Fedora Project
PackageName	weka
PackageRelease	1.fc18
PackageVersion	3.6.8
SHA-1	38CE31307DA5279F71EEB195D526690BA3B04754
SHA-256	88FD166B8C2DDA537315061B89D2E28612147FB37D805110A0F6F829CFC1069C

Key	Value
MD5	5C59A92767C1A29798188DA0EA0BF204
PackageArch	noarch
PackageDescription	Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainer	Fedora Project
PackageName	weka
PackageRelease	4.fc21
PackageVersion	3.6.8
SHA-1	3B0CF102EBA4973CCD9581B0EDDBC5F3452E36F7
SHA-256	9C1B0DBE449D56866C95B290A7B1DB976F0CC1F5D6B3D893A64920AFECC378FA

Key	Value
FileSize	6627440
MD5	66104E721852F1E0161A50B89B207C28
PackageDescription	Machine learning algorithms for data mining tasks Weka is a collection of machine learning algorithms in Java that can either be used from the command-line, or called from your own Java code. Weka is also ideally suited for developing new machine learning schemes. . Implemented schemes cover decision tree inducers, rule learners, model tree generators, support vector machines, locally weighted regression, instance-based learning, bagging, boosting, and stacking. Also included are clustering methods, and an association rule learner. Apart from actual learning schemes, Weka also contains a large variety of tools that can be used for pre-processing datasets. . This package contains the binaries and examples.
PackageMaintainer	Debian Java Maintainers <pkg-java-maintainers@lists.alioth.debian.org>
PackageName	weka
PackageSection	science
PackageVersion	3.6.14-3
SHA-1	413578EA72D0F2A5014C6B028565B5B5B69E7E30
SHA-256	58EA5EC3B42CA9719BE5756D1BD64EBED0E69D16D6FFFA200B3CEBF4CCCCAB16

Key	Value
MD5	F8ECCCB2C60182DEE962C708AD1428D3
PackageArch	noarch
PackageDescription	Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainer	Fedora Project
PackageName	weka
PackageRelease	5.fc23
PackageVersion	3.6.8
SHA-1	490362BB050D4F4F4099C962EC3664270397157F
SHA-256	0B77E79ACB6EB167DDE70BDD25D8EABA1BF085BCFCD510A45476E0A30E02FB5E

Key	Value
MD5	FFE5F74D9B859E0DE0FD6CE84F8ABB78
PackageArch	noarch
PackageDescription	Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainer	Fedora Project
PackageName	weka
PackageRelease	4.fc21
PackageVersion	3.6.8
SHA-1	51D4E7F1F480CF75BF26A21EEC6735A477EA8C58
SHA-256	9163B9492801A833EB068B42725FE300FB9994DE3BAA416F71890B51C5A76C5B