haskell-hierarchical-clustering 0.4.6-5 source package in Ubuntu

Changelog

haskell-hierarchical-clustering (0.4.6-5) unstable; urgency=medium

  [ Clint Adams ]
  * Set Rules-Requires-Root to no.

  [ Ilias Tsitsimpis ]
  * Bump debhelper compat level to 10

 -- Ilias Tsitsimpis <email address hidden>  Sun, 30 Sep 2018 21:10:59 +0300

Upload details

Uploaded by:
Debian Haskell Group on 2018-10-01
Uploaded to:
Sid
Original maintainer:
Debian Haskell Group
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Disco release on 2018-12-20 universe misc

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haskell-hierarchical-clustering_0.4.6-5.dsc 2.5 KiB b15fdfe24e5cb6a319633b1fdc472fdcc1d854b385bd224f0742fd7c4be6f63b
haskell-hierarchical-clustering_0.4.6.orig.tar.gz 10.4 KiB 75f17f09b9c38d51a208edee10da2f4706ee784b5cdfe8efc31f7f86bbcdccb1
haskell-hierarchical-clustering_0.4.6-5.debian.tar.xz 2.8 KiB 4bc6992362c4ba395ad856eb64bb53bc08ff966ede62aed7aae47738cf17a7f9

Available diffs

No changes file available.

Binary packages built by this source

libghc-hierarchical-clustering-dev: fast 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.

libghc-hierarchical-clustering-doc: fast 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.

libghc-hierarchical-clustering-prof: fast 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.