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Shark4-examples rpm build for : OpenSuSE. For other distributions click Shark4-examples.

Name : Shark4-examples
Version : 4.0.1 Vendor : obs://build_opensuse_org/science
Release : bp152.2.17 Date : 2020-04-17 04:56:09
Group : Development/Languages/C and C++ Source RPM : Shark4-4.0.1-bp152.2.17.src.rpm
Size : 47.56 MB
Packager : (none)
Summary : Examples for SHARK C++ machine learning library
Description :
This package contains some examples to use SHARK.

RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/science:/machinelearning/SLE_15_SP2_Backports/x86_64

Content of RPM  Changelog  Provides Requires

Download
ftp.icm.edu.pl  Shark4-examples-4.0.1-bp152.2.17.x86_64.rpm
     

Provides :
Shark4-examples
Shark4-examples(x86-64)

Requires :
libboost_filesystem.so.1.66.0()(64bit)
libboost_serialization.so.1.66.0()(64bit)
libboost_system.so.1.66.0()(64bit)
libc.so.6()(64bit)
libc.so.6(GLIBC_2.14)(64bit)
libc.so.6(GLIBC_2.2.5)(64bit)
libc.so.6(GLIBC_2.4)(64bit)
libgcc_s.so.1()(64bit)
libgcc_s.so.1(GCC_3.0)(64bit)
libgcc_s.so.1(GCC_3.4)(64bit)
libgomp.so.1()(64bit)
libgomp.so.1(GOMP_1.0)(64bit)
libgomp.so.1(GOMP_4.0)(64bit)
libgomp.so.1(OMP_1.0)(64bit)
libm.so.6()(64bit)
libm.so.6(GLIBC_2.2.5)(64bit)
libopenblas_pthreads.so.0()(64bit)
libshark.so.0()(64bit)
libshark0 = 4.0.1
libstdc++.so.6()(64bit)
libstdc++.so.6(CXXABI_1.3)(64bit)
libstdc++.so.6(CXXABI_1.3.8)(64bit)
libstdc++.so.6(GLIBCXX_3.4)(64bit)
libstdc++.so.6(GLIBCXX_3.4.11)(64bit)
libstdc++.so.6(GLIBCXX_3.4.15)(64bit)
libstdc++.so.6(GLIBCXX_3.4.21)(64bit)
libstdc++.so.6(GLIBCXX_3.4.9)(64bit)
rpmlib(CompressedFileNames) <= 3.0.4-1
rpmlib(FileDigests) <= 4.6.0-1
rpmlib(PayloadFilesHavePrefix) <= 4.0-1
rpmlib(PayloadIsXz) <= 5.2-1


Content of RPM :
/usr/bin/AckleyES
/usr/bin/Archive
/usr/bin/AutoencoderTutorial
/usr/bin/BinaryRBM
/usr/bin/CMAExperiment
/usr/bin/CMAPlot
/usr/bin/CMASimple
/usr/bin/CSvmGridSearchTutorial
/usr/bin/CSvmLinear
/usr/bin/CSvmMaxLikelihoodMS
/usr/bin/CSvmTutorial
/usr/bin/CVFolds
/usr/bin/Datasets
/usr/bin/DeepNetworkTrainingRBM
/usr/bin/ElitistCMASimpleMain
/usr/bin/FFNNBasicTutorial
/usr/bin/HierarchicalClustering
/usr/bin/Import
/usr/bin/KMeansTutorial
/usr/bin/KNNCrossValidationTutorial
/usr/bin/KNNTutorial
/usr/bin/KTA-tutorial
/usr/bin/KernelBudgetedSGDTutorial
/usr/bin/KernelLogisticRegression
/usr/bin/KernelRegression
/usr/bin/KernelSelection
/usr/bin/LDATutorial
/usr/bin/LassoRegression
/usr/bin/MNISTForExperts
/usr/bin/MOCMAApproximated
There is 93 files more in these RPM.

  
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