Result for 09003C639763540E17D9BF8EC92916EAB0C8FC37

Query result

Key Value
FileName./usr/share/doc/libghc-hierarchical-clustering-doc/changelog.Debian.gz
FileSize158
MD52B4E0DD6206D31964AA2ED9BD9CF5147
SHA-109003C639763540E17D9BF8EC92916EAB0C8FC37
SHA-256AD8DF6E74516DFE9B3FA2D88007A0DCC7821478CDE8321AB5E2A75D7C226B703
SSDEEP3:FttXArl6XEMltnupJmW9H3oCusA70EF6kqgAH695ZvSNMxnutLM4Pw+v8IG54/l:XtY6/tnmoOYzgo6kqguMxnutlI+wWl
TLSHT171C08C91A5F95DB8AC2AEA30A9318B97440E90622861A70143E80AC0102D5A5A3680B6
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
FileSize72222
MD51DC53B46D43B705D896E80DB8BA05A76
PackageDescriptionFast algorithms for single, average/UPGMA and complete linkage clustering. 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. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamelibghc-hierarchical-clustering-dev
PackageSectionhaskell
PackageVersion0.4.6-1
SHA-1B7690CBA60F989CE367C8F6BFCEF0D0BF4A17B68
SHA-2568CF872B40AF0B98863126852D1E4AC6A9D4B37C64913627909731EDECF562287
Key Value
FileSize32672
MD5BF8FF2B26616380BC7F58F6118C147D2
PackageDescriptionFast algorithms for single, average/UPGMA and complete linkage clustering.; documentation 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 the documentation for a library for the Haskell programming language. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamelibghc-hierarchical-clustering-doc
PackageSectiondoc
PackageVersion0.4.6-1
SHA-11EAD772B83525DFAB1E16EE5E973447D2244E894
SHA-25606DE225AEFB0668DD474255F72F2282D7D6B62598FD8D50E8C8A0B05462C00AA
Key Value
FileSize76908
MD5B16FDBB7C5C9822141C61C58AF051CCB
PackageDescriptionFast algorithms for single, average/UPGMA and complete linkage clustering. 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. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamelibghc-hierarchical-clustering-dev
PackageSectionhaskell
PackageVersion0.4.6-1
SHA-109163E85FEB47BD9FA5EFBF687AFBB20D86FB420
SHA-25678A1EC57C183323766CD6B391BF58BC7245224D951BF8564DC6929A5E19CC718