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haskell-hierarchical-clustering package

haskell-hierarchical-clustering 0.4.7-3 source package in Ubuntu

Changelog

haskell-hierarchical-clustering (0.4.7-3) unstable; urgency=medium

  * Remove retired developer, Joachim Breitner, from Uploaders.
  * Declare compliance with Debian policy 4.6.2
  * Fix FTBFS with GHC 9.4

 -- Ilias Tsitsimpis <email address hidden>  Thu, 31 Aug 2023 17:56:37 +0300

Upload details

Uploaded by:
Debian Haskell Group
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
Noble release universe misc

Downloads

File Size SHA-256 Checksum
haskell-hierarchical-clustering_0.4.7-3.dsc 2.5 KiB 86fdf03696af889b176f370c69fc3236057b4d8721838aefa6c278e39956924e
haskell-hierarchical-clustering_0.4.7.orig.tar.gz 10.4 KiB 138f46160ee436293326a575bf6fd3caceb6dc7b91164d78a02582c6e0c6d195
haskell-hierarchical-clustering_0.4.7-3.debian.tar.xz 3.3 KiB 1e203c6caa5773046e6f84f91773b8e41e8859ada958ec0ebe5fbd2cab6dad02

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.