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haskell-hierarchical-clustering package

haskell-hierarchical-clustering 0.4.6-6 source package in Ubuntu

Changelog

haskell-hierarchical-clustering (0.4.6-6) unstable; urgency=medium

  * Patch for newer deps

 -- Gianfranco Costamagna <email address hidden>  Sat, 03 Aug 2019 12:15:26 +0200

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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
Focal release universe misc

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File Size SHA-256 Checksum
haskell-hierarchical-clustering_0.4.6-6.dsc 2.5 KiB 3aa8b1f4febfcb372638f91b6e20393acd9381c14e149f882d1a5080d4fed5a1
haskell-hierarchical-clustering_0.4.6.orig.tar.gz 10.4 KiB 75f17f09b9c38d51a208edee10da2f4706ee784b5cdfe8efc31f7f86bbcdccb1
haskell-hierarchical-clustering_0.4.6-6.debian.tar.xz 3.1 KiB c482da74d8927ea1cb38bf2d75bec68ef69e56b523d4d238a88d985798654a64

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Binary packages built by this source

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

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

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

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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.