| Key | Value |
|---|---|
| CRC32 | 38E2CED6 |
| FileName | CHANGELOG-3-6-6 |
| FileSize | 23989 |
| MD5 | 20AA328C5F65553F5858BC3391DC976E |
| 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 | 1A44918EC980414BB8EBFB0BCABEE9CE584ADFFF |
| SHA-256 | 36FEC9F870465E0D2E3574B6DFF191E7AF7B8BBBC6A40144675BF7E5AD9A8EC7 |
| SSDEEP | 384:STEnOxczPctNkPBP2a+BVxbG+zKfIaYeYMvUf5TdLOiStlnCHNZ8AjucG8VMk25Z:STEnSczPctNkPBPH+BV1pzKfIaYeYMcG |
| SpecialCode | |
| TLSH | T132B20F87FE1D28F223F7C1C513146AABD61280F9F39582B27A8C4529119A05176FEF9F |
| db | nsrl_modern_rds |
| insert-timestamp | 1646988215.239775 |
| source | NSRL |
| hashlookup:parent-total | 19 |
| hashlookup:trust | 100 |
The searched file hash is included in 19 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 | 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 | EA74E950EC5AA4A7ED2034FDA6C84F78 |
| PackageArch | noarch |
| PackageDescription | Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data-set 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 | 2.fc24 |
| PackageVersion | 3.6.13 |
| SHA-1 | 59DABF4634BC1455F0829472D885642D723CB691 |
| SHA-256 | 43E9B28D52B8E0FDA22EB4285AAD30FB1B571878FF6E71B0661FD2559796AE3A |
| Key | Value |
|---|---|
| MD5 | CD0408AAA1278EB00772B57B3B486E94 |
| 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 | 629B06A9D4ABCDFD85197F2D9EC019584B6ED858 |
| SHA-256 | 274128B950462B9FC9525F2720AA541AABF47CCE3CF15841AFAB8583DA800153 |
| Key | Value |
|---|---|
| MD5 | 57916F9F0F22747C82146D04D3A07337 |
| 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 | 93C62B0C55ECDD9C1FCA96FE2363B7178A1CAD60 |
| SHA-256 | 696C09804D21839E9985A09D6B930AD401C63C9FF87C363B4EA6EA1630992F0E |
| Key | Value |
|---|---|
| MD5 | 8A02F78C8216CA0B6115E9E4714C56F7 |
| 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 | 2.fc19 |
| PackageVersion | 3.6.8 |
| SHA-1 | 9E020CBDD4B530ED7EB81026D3B0E73A52BAC311 |
| SHA-256 | 65E746AFF34A2BE74B972E1468388503EE72A47A43C8A6D694EB327CF0D3A139 |
| Key | Value |
|---|---|
| MD5 | BC666A98F1DEC32B39A518F4FFB0D25D |
| 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 | 2.fc19 |
| PackageVersion | 3.6.8 |
| SHA-1 | A00DACDE10CF09DDAC4EA6469EBFE4268756B5E6 |
| SHA-256 | E69CDB9626642659D135F68EB83DE98725FF3182A9275B1625EB7A4DE0D9E6AC |