Result for EBEA6DB6B5DAF39395C181E984563757CFF40C2F

Query result

Key Value
FileName./usr/share/doc/libghc-hierarchical-clustering-doc/changelog.Debian.gz
FileSize470
MD59AABE4BC634EFE6D63ECC6EDC06CE0F0
SHA-1EBEA6DB6B5DAF39395C181E984563757CFF40C2F
SHA-25604F98368DEB54145CC8C3DC100F6724FBB1E4037899CFA5EDA6F3EEC4D3B358F
SSDEEP12:XwvyO3B4c4+cFEbKcAxyWSo6mkEVMy4vUzwy3ot8bMw:Xu5B/4UbKcAxyWSo6mkeMy9zwy3ot8bX
TLSHT126F0D41732A4F950DAC58DB06B80D14311A5967A70CE70915F637770917E1C9D159476
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
FileSize79976
MD5136B4C11AAF1404C288954174FC7215B
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
PackageVersion0.4.6-3build1
SHA-142AF1E6CAC552D454914250CCBDC1F1A112E77EB
SHA-25682046733D7276B194749AF59843547738C0D7E20B1AC0A407A4180A822FFB762
Key Value
FileSize84038
MD51D4B604B3E11E30B735A67064170D8E6
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
PackageVersion0.4.6-3build1
SHA-1B9467D0943F01F3E16DD21D193DBBB52C788A1D1
SHA-2565D8DDFB43F2A99F9A8346B163C184AC5B07301C6B193D0C34DC24AF34DC3A2F0
Key Value
FileSize34228
MD5A835A9D23E198B5B3B777570233D966C
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
PackageVersion0.4.6-3build1
SHA-16B1631D6F0CF6D4FF0F3C9DDD43F9E937AC50AF0
SHA-256ECBBC054C285C2F922DBF7D0C9D3E347A48F67337693A8C4099254F3BAB0D4A5