Result for 2BE923A05D458995FD2CA5D2362CD5626FCE91CB

Query result

Key Value
CRC326CA56957
FileNamecpu.with.vendor.arff
FileSize6939
MD56A1A6C5781CF2F368946F44969C94DC1
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-12BE923A05D458995FD2CA5D2362CD5626FCE91CB
SHA-2563E527251DCA4F1A2BC6C289A2E814F49BA7ECDB19315FB7CE9DDBF5AAD248816
SSDEEP192:blGGucOWagBE57JuhOUJNSMIywTSCBWYyGEq8YfRgn8r:blGGulvJjywTSC3yGEq8Y28r
SpecialCode
TLSHT18CE18D336254066BF19A8AD1F7A83C0544BCF0A3E55C0E14E7B273991E9D9E360F5B27
dbnsrl_modern_rds
insert-timestamp1646994768.7220628
sourceNSRL
hashlookup:parent-total43
hashlookup:trust100

Network graph view

Parents (Total: 43)

The searched file hash is included in 43 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5AF0A80E55F0A2DD9AF82748F486D8147
PackageArchnoarch
PackageDescriptionWeka 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.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease5.fc15
PackageVersion3.6.2
SHA-105C95A1E4C199FFD0AF520272D66C5C259D5C690
SHA-2567032BCD9F1F36009185E154D702650590D725E2F634F34CA12F61B7868F22BDA
Key Value
MD5FB0FDC148881D2057ED6FD3B3B86138D
PackageArchnoarch
PackageDescriptionWeka 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.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease1.fc18
PackageVersion3.6.8
SHA-10B8CB68B514D3C4025099E0DB6A462AAED99D026
SHA-2563D35131B632B13C0EEE5EE12D6A525DE6C4F90FEF6ED1F3839056C2AA131FB6A
Key Value
MD56CA942E1743D91DED4B1BFD08D9AF700
PackageArchx86_64
PackageDescriptionAn 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/>.
PackageNameR-RWeka
PackageRelease1.123
PackageVersion0.4.39
SHA-10E40454308D759B3F7D76AC6CA2EE8C7B9BE7D65
SHA-256DD04AF53C3BA3674FEC64E770440628FD9F92B9E062972FDF719109A60E0167A
Key Value
MD56CC4BB080A104D66E2BD639683C06D63
PackageArchnoarch
PackageDescriptionWeka 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.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease6.fc17
PackageVersion3.6.2
SHA-11E29FADF4F5D8F231B0A3A4B67F1025E40B3D15B
SHA-2562904DDA4EF487E5F2E7BCA470D978EAE0E90DEA812ADE60D3BB368A43EC0BCDC
Key Value
MD526BC7C70CBB10CC5B371354932D201BA
PackageArchx86_64
PackageDescriptionAn 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/>.
PackageNameR-RWeka
PackageRelease1.14
PackageVersion0.4.39
SHA-1200251EF4DF12DC8E8A4ED2D0B62AA914777F89E
SHA-256F638E265C4C7F06E3F5FFC874B2D359977109BC2FC2510E031892828C5C27096
Key Value
MD5F682D20D190BC1A32EE58A4D1E90DCA9
PackageArchx86_64
PackageDescriptionAn 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/>.
PackageNameR-RWeka
PackageReleaselp151.1.58
PackageVersion0.4.39
SHA-1222C4EADFBCFCE6387D5FE33A3D3EA2DAAD80639
SHA-25609DB681F992626D0F6764B66D264E3AE03692E9E910604B81D4CFFF04990C435
Key Value
MD559655A970FA1B2742F2C7F6971433C89
PackageArchnoarch
PackageDescriptionWeka 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.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease5.fc15
PackageVersion3.6.2
SHA-12737AAE6672EE0E774A4945C9559956FE8D22B98
SHA-256FE1E281FD02276E615A9A2E09039F8FC5915E4BE721AA0C18BC9C13CCA242496
Key Value
MD55EA8EB2849C90A6BDD85FC2DF0DA2A87
PackageArchi586
PackageDescriptionAn 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/>.
PackageNameR-RWeka
PackageRelease1.93
PackageVersion0.4.39
SHA-13154BF2E77CA73DF6CDA29FA429B2E206CA03B51
SHA-25627D1DA71A1D553BF5D66C4E006B817B8A7ACF516B4F5A5FDCF60F49374EE8D69
Key Value
MD53E729A70F089D3A2D172340F3C5596CE
PackageArchnoarch
PackageDescriptionWeka 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.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease1.fc18
PackageVersion3.6.8
SHA-138CE31307DA5279F71EEB195D526690BA3B04754
SHA-25688FD166B8C2DDA537315061B89D2E28612147FB37D805110A0F6F829CFC1069C
Key Value
MD55C59A92767C1A29798188DA0EA0BF204
PackageArchnoarch
PackageDescriptionWeka 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.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease4.fc21
PackageVersion3.6.8
SHA-13B0CF102EBA4973CCD9581B0EDDBC5F3452E36F7
SHA-2569C1B0DBE449D56866C95B290A7B1DB976F0CC1F5D6B3D893A64920AFECC378FA