Key | Value |
---|---|
CRC32 | 6CA56957 |
FileName | cpu.with.vendor.arff |
FileSize | 6939 |
MD5 | 6A1A6C5781CF2F368946F44969C94DC1 |
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 | 2BE923A05D458995FD2CA5D2362CD5626FCE91CB |
SHA-256 | 3E527251DCA4F1A2BC6C289A2E814F49BA7ECDB19315FB7CE9DDBF5AAD248816 |
SSDEEP | 192:blGGucOWagBE57JuhOUJNSMIywTSCBWYyGEq8YfRgn8r:blGGulvJjywTSC3yGEq8Y28r |
SpecialCode | |
TLSH | T18CE18D336254066BF19A8AD1F7A83C0544BCF0A3E55C0E14E7B273991E9D9E360F5B27 |
db | nsrl_modern_rds |
insert-timestamp | 1646994768.7220628 |
source | NSRL |
hashlookup:parent-total | 43 |
hashlookup:trust | 100 |
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 |
---|---|
MD5 | AF0A80E55F0A2DD9AF82748F486D8147 |
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.fc15 |
PackageVersion | 3.6.2 |
SHA-1 | 05C95A1E4C199FFD0AF520272D66C5C259D5C690 |
SHA-256 | 7032BCD9F1F36009185E154D702650590D725E2F634F34CA12F61B7868F22BDA |
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 | 6CC4BB080A104D66E2BD639683C06D63 |
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 | 6.fc17 |
PackageVersion | 3.6.2 |
SHA-1 | 1E29FADF4F5D8F231B0A3A4B67F1025E40B3D15B |
SHA-256 | 2904DDA4EF487E5F2E7BCA470D978EAE0E90DEA812ADE60D3BB368A43EC0BCDC |
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 | 59655A970FA1B2742F2C7F6971433C89 |
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.fc15 |
PackageVersion | 3.6.2 |
SHA-1 | 2737AAE6672EE0E774A4945C9559956FE8D22B98 |
SHA-256 | FE1E281FD02276E615A9A2E09039F8FC5915E4BE721AA0C18BC9C13CCA242496 |
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 |