Result for 01EAD43FF02A86C1032DA3D86100F87CC8EBB1F3

Query result

Key Value
FileName./usr/share/doc/python-pebl-1.0.2/html/discretizer.html
FileSize6427
MD5CEBCE515E411480E4F51B75F0646B9D5
SHA-101EAD43FF02A86C1032DA3D86100F87CC8EBB1F3
SHA-256B0576326309034114BFC8A04F94D32A1681A3E0EE1F76A6C04B672CD15A3D6D5
SSDEEP96:I06fF0MRD3MD9ljm0niUD16EEASUu1QKZAQmfpwDAVlSgo1TYDKjmcniKD16rL:KFTRkg0nvhktQCpmfWYS91KcnLh+
TLSHT1F3D1A62D95F0A933480655E3DAF15A21BC92D1ABE206150CB1EC526DAFC7FA28E1734E
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5199B2A76C34980D7D64356BBE0D7110E
PackageArchs390
PackageDescriptionPebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations. Pebl includes the following features: - can learn with observational and interventional data - handles missing values and hidden variables using exact and heuristic methods - provides several learning algorithms; makes creating new ones simple - has facilities for transparent parallel execution using several cluster/grid resources - calculates edge marginals and consensus networks - presents results in a variety of formats
PackageMaintainerFedora Project
PackageNamepython-pebl
PackageRelease7.fc17
PackageVersion1.0.2
SHA-15C0525C1EF205CEF2CBFF99F841D2EBE33EC9C22
SHA-256C0239568E2F031687050D6C3702F4B3304B0CD1A1C1AA05858B9BAE927C57DEE
Key Value
MD5C703F501977D6200CDB1ED253EDA8EAA
PackageArchs390x
PackageDescriptionPebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations. Pebl includes the following features: - can learn with observational and interventional data - handles missing values and hidden variables using exact and heuristic methods - provides several learning algorithms; makes creating new ones simple - has facilities for transparent parallel execution using several cluster/grid resources - calculates edge marginals and consensus networks - presents results in a variety of formats
PackageMaintainerFedora Project
PackageNamepython-pebl
PackageRelease7.fc17
PackageVersion1.0.2
SHA-179F4C780FB1BF6C4FF42A453E79DBBD576ED38E4
SHA-2569E2159553FB929FF0D9D0C5A1F71175CFE5CC56A576381607D8CD8861E56E2EA