Result for 001DEF5C97FCFAFFA7A9DBE9F1F9F7B28FDB0CF2

Query result

Key Value
FileName./usr/share/doc/weka/changelogs/CHANGELOG-3-6-4
FileSize9531
MD5BB13B47AA8E5DC29D722752C5DCFEED0
SHA-1001DEF5C97FCFAFFA7A9DBE9F1F9F7B28FDB0CF2
SHA-25648261BEE9DD77E07C78398E8196E946D53D4290ADF591A111ADEFE1E1E1117D3
SSDEEP96:Lbj1h4gc2SUli8wDWruAVR+aH22AQxJlrpFWSZapBspB7e8p4Ssz8HYsI+Ym7Au7:ozUsDWrumRnpnZCOsKf7Mvxq05tGqT0
TLSHT1621252A7FE0E2AB127A3C1C112493696D726D0FDE782527138CC8854069A55473FEFAB
hashlookup:parent-total19
hashlookup:trust100

Network graph view

Parents (Total: 19)

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
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
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
Key Value
MD5F8ECCCB2C60182DEE962C708AD1428D3
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.fc23
PackageVersion3.6.8
SHA-1490362BB050D4F4F4099C962EC3664270397157F
SHA-2560B77E79ACB6EB167DDE70BDD25D8EABA1BF085BCFCD510A45476E0A30E02FB5E
Key Value
MD5FFE5F74D9B859E0DE0FD6CE84F8ABB78
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-151D4E7F1F480CF75BF26A21EEC6735A477EA8C58
SHA-2569163B9492801A833EB068B42725FE300FB9994DE3BAA416F71890B51C5A76C5B
Key Value
MD5EA74E950EC5AA4A7ED2034FDA6C84F78
PackageArchnoarch
PackageDescriptionWeka 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.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease2.fc24
PackageVersion3.6.13
SHA-159DABF4634BC1455F0829472D885642D723CB691
SHA-25643E9B28D52B8E0FDA22EB4285AAD30FB1B571878FF6E71B0661FD2559796AE3A
Key Value
MD5CD0408AAA1278EB00772B57B3B486E94
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-1629B06A9D4ABCDFD85197F2D9EC019584B6ED858
SHA-256274128B950462B9FC9525F2720AA541AABF47CCE3CF15841AFAB8583DA800153
Key Value
MD557916F9F0F22747C82146D04D3A07337
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-193C62B0C55ECDD9C1FCA96FE2363B7178A1CAD60
SHA-256696C09804D21839E9985A09D6B930AD401C63C9FF87C363B4EA6EA1630992F0E
Key Value
MD58A02F78C8216CA0B6115E9E4714C56F7
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
PackageRelease2.fc19
PackageVersion3.6.8
SHA-19E020CBDD4B530ED7EB81026D3B0E73A52BAC311
SHA-25665E746AFF34A2BE74B972E1468388503EE72A47A43C8A6D694EB327CF0D3A139
Key Value
MD5BC666A98F1DEC32B39A518F4FFB0D25D
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
PackageRelease2.fc19
PackageVersion3.6.8
SHA-1A00DACDE10CF09DDAC4EA6469EBFE4268756B5E6
SHA-256E69CDB9626642659D135F68EB83DE98725FF3182A9275B1625EB7A4DE0D9E6AC