Parents (Total: 6)

The searched file hash is included in 6 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	1170318
MD5	1F645FC65FD190B34EC64C5F6B3593DC
PackageDescription	Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) . This package contains the Python 3 version.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-sklearn
PackageSection	python
PackageVersion	0.17.0-4
SHA-1	66D45DAAE442CB9D4FF2F78D008DFD125BBD991F
SHA-256	972C825D88117430F5B1CE5B58BC90E14FD21A358D4787888BBC1D1DFB3ACA40

Key	Value
FileSize	1170636
MD5	133EE2618D9C2EAE052563A50D2A305A
PackageDescription	Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM)
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-sklearn
PackageSection	python
PackageVersion	0.17.0-4
SHA-1	A733081046A9F2578A1645BDB642B5D10306B4D8
SHA-256	73CF1C6E22AAAE852C9C8537C2587FFF24A4A6245E201959CED05C414C43BB9A

Key	Value
MD5	BCF32221C8DD22DF9CFE204375B750A2
PackageArch	ppc64
PackageDescription	Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.
PackageMaintainer	Fedora Project
PackageName	python3-scikit-learn
PackageRelease	4.fc24
PackageVersion	0.17.1
SHA-1	547DB711D4863545256C4D84E1B956593497B713
SHA-256	76E3540F2E6683CF0BC08CBA78A3756E50A04EB5661067EBAA99481A5CAA6759

Key	Value
MD5	1AE3D0B8B4B0593EC9818531CBB660EA
PackageArch	aarch64
PackageDescription	Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.
PackageMaintainer	Fedora Project
PackageName	python2-scikit-learn
PackageRelease	4.fc24
PackageVersion	0.17.1
SHA-1	7AC2D03BDB0E3CB39425A261B253DF8F452A7B9E
SHA-256	8063B84C4F1AC5EB381AFF51FA1086878E77C3C60EEB5D4AE2454CD3DED826D2

Key	Value
MD5	0C4F32374415CCDA8D571AA31F3D20B1
PackageArch	aarch64
PackageDescription	Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.
PackageMaintainer	Fedora Project
PackageName	python3-scikit-learn
PackageRelease	4.fc24
PackageVersion	0.17.1
SHA-1	5513BD93A3C3B030CC6500A683EF48326EB21E74
SHA-256	13F962CFADEE43B02880D50748E7A8B387D2C1BC7A41D66A0C868B48D85D09C4

Key	Value
MD5	9397956255C7AF2946DEB3BCD69CA260
PackageArch	ppc64
PackageDescription	Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.
PackageMaintainer	Fedora Project
PackageName	python2-scikit-learn
PackageRelease	4.fc24
PackageVersion	0.17.1
SHA-1	029E2D6D842ACC8F5BF9A50BBFA6EE847902189C
SHA-256	880E8AC446B5B246648AAFAC6AFC602AEE63F7C6377B9A8C7C7F61849C008326