| Key | Value |
|---|---|
| FileName | ./usr/share/doc/weka/changelogs/CHANGELOG-3-6-4 |
| FileSize | 9531 |
| MD5 | BB13B47AA8E5DC29D722752C5DCFEED0 |
| SHA-1 | 001DEF5C97FCFAFFA7A9DBE9F1F9F7B28FDB0CF2 |
| SHA-256 | 48261BEE9DD77E07C78398E8196E946D53D4290ADF591A111ADEFE1E1E1117D3 |
| SSDEEP | 96:Lbj1h4gc2SUli8wDWruAVR+aH22AQxJlrpFWSZapBspB7e8p4Ssz8HYsI+Ym7Au7:ozUsDWrumRnpnZCOsKf7Mvxq05tGqT0 |
| TLSH | T1621252A7FE0E2AB127A3C1C112493696D726D0FDE782527138CC8854069A55473FEFAB |
| 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 |
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| 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 |
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| 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 |
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| PackageVersion | 3.6.8 |
| SHA-1 | 490362BB050D4F4F4099C962EC3664270397157F |
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| Key | Value |
|---|---|
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| 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 |
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| PackageVersion | 3.6.8 |
| SHA-1 | 51D4E7F1F480CF75BF26A21EEC6735A477EA8C58 |
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| Key | Value |
|---|---|
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| 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 |
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| SHA-1 | 59DABF4634BC1455F0829472D885642D723CB691 |
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| 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 |
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| Key | Value |
|---|---|
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| 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 |
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| PackageMaintainer | Fedora Project |
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