Parents (Total: 7)

The searched file hash is included in 7 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	680CB2A8BD3C4EB6A760CD2F17D13CB7
PackageArch	s390x
PackageDescription	Pebl 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
PackageMaintainer	Fedora Project
PackageName	python-pebl
PackageRelease	9.fc18
PackageVersion	1.0.2
SHA-1	CC718AD0C8B54E0A8037B241D9AA5172EC3C9049
SHA-256	72813ACFC93464A7B0F1010778E466A80899A0E6B4FBC5631493852FBACE2583

Key	Value
MD5	73EEB5D575C87E19A776A4C6F0E5D682
PackageArch	s390x
PackageDescription	Pebl 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
PackageMaintainer	Fedora Project
PackageName	python-pebl
PackageRelease	10.fc19
PackageVersion	1.0.2
SHA-1	5DB1211F169CE9DF91A8753BF5C47585D2B58EE1
SHA-256	860FB2F9027F081A1E96CDB2E5DCB79A4674C2DB8F96C10A7C53D9A5E3357613

Key	Value
MD5	C703F501977D6200CDB1ED253EDA8EAA
PackageArch	s390x
PackageDescription	Pebl 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
PackageMaintainer	Fedora Project
PackageName	python-pebl
PackageRelease	7.fc17
PackageVersion	1.0.2
SHA-1	79F4C780FB1BF6C4FF42A453E79DBBD576ED38E4
SHA-256	9E2159553FB929FF0D9D0C5A1F71175CFE5CC56A576381607D8CD8861E56E2EA

Key	Value
MD5	1431624840F377D2B60AE86BA3B48125
PackageArch	ppc64
PackageDescription	Pebl 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
PackageMaintainer	Fedora Project
PackageName	python-pebl
PackageRelease	10.fc19
PackageVersion	1.0.2
SHA-1	695BC0A721BCFA496A46E3FE079B217FE469C1B5
SHA-256	99755AFD9CC9DCA8556401A62F358456D3B2BDCFA0E3F55E7DAA6D3827355E6B

Key	Value
MD5	09514D7D4FF7DF3CDFE1886463063ECA
PackageArch	ppc64
PackageDescription	Pebl 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
PackageMaintainer	Koji
PackageName	python-pebl
PackageRelease	9.fc18
PackageVersion	1.0.2
SHA-1	39CBE24517200AAD70554C10907478A0DFC73F49
SHA-256	A992C5AC77B150182399C81E94B4BD68BA3D063933050AB38D8A2CFC1253B6B4

Key	Value
MD5	BD91E2A6307FBE9B7A69EF91A3FC65C6
PackageArch	ppc64
PackageDescription	Pebl 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
PackageMaintainer	Koji
PackageName	python-pebl
PackageRelease	7.fc17
PackageVersion	1.0.2
SHA-1	E7E2B7120692DBA7EAB8B0C8264E91347AB138F7
SHA-256	D1171014600F3AD1D1A3EE0F31D31EC7693F0585C05AFD0D5EA0D1F65B1570FC

Key	Value
MD5	1C0EBED9DF2D3608F2F1A32C851D57C2
PackageArch	s390x
PackageDescription	Pebl 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
PackageMaintainer	Fedora Project
PackageName	python-pebl
PackageRelease	7.fc15
PackageVersion	1.0.2
SHA-1	0FA2BF96EC9F29BA6451956D7CB708CED0344E94
SHA-256	9EFDD1BCC87B23BABDB686D5924EB437CD7AECA504EF0EC6885F121EA8AA09DD