Result for 3285255FFB237467A1845C4465F1CA4BBFEEA89C

Query result

Key	Value
CRC32	DCCA98BD
FileName	ionosphere.arff
FileSize	80385
MD5	120D04F88C916DF566C448D0D9167649
OpSystemCode	{'MfgCode': '1006', 'OpSystemCode': '362', 'OpSystemName': 'TBD', 'OpSystemVersion': 'none'}
ProductCode	{'ApplicationType': 'Data', 'Language': 'English', 'MfgCode': '80467', 'OpSystemCode': '884', 'ProductCode': '13571', 'ProductName': 'Weka', 'ProductVersion': '3.6'}
SHA-1	3285255FFB237467A1845C4465F1CA4BBFEEA89C
SHA-256	298BCED6370DC4AC4FA8B5226410C9FCD61521F3C88CEB14200808B8319325CB
SSDEEP	1536:JXs4fGBZGEdoN2xqyHe4t03pJXhsKOT6JHdnOe2:JvaD82hSa
SpecialCode
TLSH	T11B731F7F43DE8AD7BD5D53A896EB0DD33392D097B044ECCC536AAC89A805EC72238546
db	nsrl_modern_rds
insert-timestamp	1646997008.3927422
source	NSRL
hashlookup:parent-total	31
hashlookup:trust	100

Network graph view

Parents (Total: 31)

The searched file hash is included in 31 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
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

Key	Value
MD5	B09606CE0CEEAC84364799F8F2756AE5
PackageArch	armv7hl
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	1.90
PackageVersion	0.4.39
SHA-1	621B161255589D894AB04D6385CDD4DAB772C932
SHA-256	515A84651B21E739620DE03F57DE70D4E9FDB5EF69BAB27CCEE08EBF7CD26BCD