Result for 00166F4E8042D35B50021C754B21807F72801D6A

Query result

Key Value
FileName./usr/share/doc/shogun-doc-cn/html_cn/search/functions_7e.html
FileSize1019
MD5694302D0436C213BB94D41D75F04CD04
SHA-100166F4E8042D35B50021C754B21807F72801D6A
SHA-2565632EE5EAB4AA92C2261DF7F0B2480234B55796D50CEED17965513516F0CBC50
SSDEEP24:hMNmArDJMlnVvPwV4NOflXWBTrO45oRRpys+RRNysxX8ra4IB4X:ImqGlRnNOlLHtys+xysxX8rtfX
TLSHT18511CE176C068915846245E0F0F1EB1DBCB4DE34A70EC89818EC81D7E1C2FD8CC19BAA
hashlookup:parent-total5
hashlookup:trust75

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Parents (Total: 5)

The searched file hash is included in 5 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD51BD49A3C54C47DADA9C782A9606715ED
PackageArchppc64le
PackageDescriptionThis package contains the documentation-files for rapidjson.
PackageMaintainerFedora Project
PackageNamerapidjson-doc
PackageRelease2.el7
PackageVersion1.1.0
SHA-16751302F4AE23A3A1FDCE24AEF0CD45D72390BE8
SHA-25600B9067ABF12944BD57DF7D7A5260E3DADC9BF8E3570FB694AA0B1853F838D8B
Key Value
MD505DD9CA61BC4D8A34562058246750D74
PackageArchx86_64
PackageDescriptionThis package contains the documentation-files for rapidjson.
PackageMaintainerFedora Project
PackageNamerapidjson-doc
PackageRelease2.el7
PackageVersion1.1.0
SHA-1E442C169604EC031C4C8F018F067919EBD439AB2
SHA-2569D5E9C6CAE1AD489568ACF5A554A253575294EE6ABC456950DAC928BBAE6FCF5
Key Value
MD59F04C76FC1006F651A11CC10CC30A0AA
PackageArchaarch64
PackageDescriptionThis package contains the documentation-files for rapidjson.
PackageMaintainerFedora Project
PackageNamerapidjson-doc
PackageRelease2.el7
PackageVersion1.1.0
SHA-1E2C669A50B057C191E64107458094FAF9941A42A
SHA-256DDF4345DE3AC11E37DB233D51795D6E6EB4AC1A1354067AA6C10C7F25733067E
Key Value
FileSize23788930
MD5FD9D72B20B307B7432B20371D1E1BB9F
PackageDescriptionLarge Scale Machine Learning Toolbox SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing. . SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the Chinese user and developer documentation.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNameshogun-doc-cn
PackageSectiondoc
PackageVersion3.1.1-1
SHA-1FD7CAA9393703342ABC98013EFCA96EA573FC933
SHA-256D4D9AE27A2CA3E1834719889F724BC790E02250BB2050B6F7CC53E13A8DA0CEF
Key Value
MD5B857D26A86922D1A1384D163BC4A4EEF
PackageArchppc64
PackageDescriptionThis package contains the documentation-files for rapidjson.
PackageMaintainerFedora Project
PackageNamerapidjson-doc
PackageRelease2.el7
PackageVersion1.1.0
SHA-1C123BF1F60F35AB3D439DBBC12CF827592E86606
SHA-256DD8DC8776269A6590AB1A67DB63A5F7F525212525BAA6D067726A81C3B5E8CA5