Result for E4FB8E42EAA67199EB334A592FF5F3BF403D13CB

Query result

Key Value
FileName./usr/lib/haskell-packages/ghc/lib/s390x-linux-ghc-8.0.1/hierarchical-clustering-0.4.6-Ap6qE3Og6fLFLNSA7PLC94/Data/Clustering/Hierarchical.p_hi
FileSize4327
MD509E31094C916745A3245BFABC8E9D2A3
SHA-1E4FB8E42EAA67199EB334A592FF5F3BF403D13CB
SHA-256546F4515589EA57B4635B109A64A8D3509EBCDE6FF8DB4BB887CCB0A2A9BEFFE
SSDEEP96:nqsIZxRjuAiA08OgARELYEsoc0zzuMDvV7:LenKwmy19J
TLSHT10991414DAFA1C92FE8160E78687B87043B70F69166529F43C1E874B18C26FD42E7116A
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize112816
MD5C9F7B477D96AB7D926E817118568BDB7
PackageDescriptionfast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides a library for the Haskell programming language, compiled for profiling. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerDebian Haskell Group <pkg-haskell-maintainers@lists.alioth.debian.org>
PackageNamelibghc-hierarchical-clustering-prof
PackageSectionhaskell
PackageVersion0.4.6-3+b1
SHA-177142EC3FC3D6AFBE38C728E6AF1A956C9E78B8E
SHA-256E36736CAA32097439EE647E5B06B7D872B91E400DD0DB55E3C7DE6350E6BF3DE
Key Value
FileSize96880
MD59B9DECCE9DEA7EE0F86A109F812D0A5F
PackageDescriptionfast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides a library for the Haskell programming language, compiled for profiling. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerDebian Haskell Group <pkg-haskell-maintainers@lists.alioth.debian.org>
PackageNamelibghc-hierarchical-clustering-prof
PackageSectionhaskell
PackageVersion0.4.6-3+b1
SHA-106F1A9E90BA18DC8FEEFA7B23C75244E346CB7B3
SHA-256152530EA7C0355A88FCA266A6E60DF56B41AD2EAB42032DC991A5BE2E83ADD4D
Key Value
FileSize102982
MD5170CA2540250C8851EC99D2E027AFEE6
PackageDescriptionfast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides a library for the Haskell programming language, compiled for profiling. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerDebian Haskell Group <pkg-haskell-maintainers@lists.alioth.debian.org>
PackageNamelibghc-hierarchical-clustering-prof
PackageSectionhaskell
PackageVersion0.4.6-3+b1
SHA-16BA7E78A47CE08347D718D90C8210F3B35B12653
SHA-256FADCE9E0C8F39AFD7EF8944E547D9D1FE2A3FCD362F67FF4A639021CD688D344