haskell-hierarchical-clustering 0.4.6-1 source package in Ubuntu

Changelog

haskell-hierarchical-clustering (0.4.6-1) unstable; urgency=low

  * Initial release

 -- Joachim Breitner <email address hidden>  Wed, 09 Dec 2015 23:01:24 +0100

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Uploaded by:
Debian Haskell Group on 2015-12-11
Uploaded to:
Sid
Original maintainer:
Debian Haskell Group
Architectures:
any all
Section:
misc
Urgency:
Low Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Xenial release on 2015-12-19 universe misc

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haskell-hierarchical-clustering_0.4.6-1.dsc 2.4 KiB 33c84d9a8927e8016c744fed812d1681b0cea6965a3342cd4cc7c653e9fe031d
haskell-hierarchical-clustering_0.4.6-1.debian.tar.xz 2.3 KiB 9d5710efea03e2641f27d46b4b951c4e6f60e85f1545426400e72dac23c10801
haskell-hierarchical-clustering_0.4.6.orig.tar.gz 10.4 KiB 75f17f09b9c38d51a208edee10da2f4706ee784b5cdfe8efc31f7f86bbcdccb1

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Binary packages built by this source

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

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

libghc-hierarchical-clustering-doc: No summary available for libghc-hierarchical-clustering-doc in ubuntu zesty.

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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.