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haskell-hierarchical-clustering package

haskell-hierarchical-clustering 0.4.7-1build2 source package in Ubuntu

Changelog

haskell-hierarchical-clustering (0.4.7-1build2) hirsute; urgency=medium

  * No-change rebuild for new GHC ABIs

 -- Steve Langasek <email address hidden>  Thu, 29 Oct 2020 20:32:48 +0000

Upload details

Uploaded by:
Steve Langasek
Uploaded to:
Hirsute
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Jammy release universe misc

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File Size SHA-256 Checksum
haskell-hierarchical-clustering_0.4.7.orig.tar.gz 10.4 KiB 138f46160ee436293326a575bf6fd3caceb6dc7b91164d78a02582c6e0c6d195
haskell-hierarchical-clustering_0.4.7-1build2.debian.tar.xz 3.1 KiB 6abab937072f6dec96d4308c79c3d99078f0d8d3c174a89c520f435c70e16bb7
haskell-hierarchical-clustering_0.4.7-1build2.dsc 2.6 KiB 3e5bb7dac52bd23cf954eda127813c540ef3ee7401544ce0cf5c097aeb60dc3b

Available diffs

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Binary packages built by this source

libghc-hierarchical-clustering-dev: No summary available for libghc-hierarchical-clustering-dev in ubuntu hirsute.

No description available for libghc-hierarchical-clustering-dev in ubuntu hirsute.

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.