How to Install and Uninstall libghc-hierarchical-clustering-prof Package on Ubuntu 21.04 (Hirsute Hippo)
Last updated: November 26,2024
1. Install "libghc-hierarchical-clustering-prof" package
Please follow the steps below to install libghc-hierarchical-clustering-prof on Ubuntu 21.04 (Hirsute Hippo)
$
sudo apt update
Copied
$
sudo apt install
libghc-hierarchical-clustering-prof
Copied
2. Uninstall "libghc-hierarchical-clustering-prof" package
Please follow the instructions below to uninstall libghc-hierarchical-clustering-prof on Ubuntu 21.04 (Hirsute Hippo):
$
sudo apt remove
libghc-hierarchical-clustering-prof
Copied
$
sudo apt autoclean && sudo apt autoremove
Copied
3. Information about the libghc-hierarchical-clustering-prof package on Ubuntu 21.04 (Hirsute Hippo)
Package: libghc-hierarchical-clustering-prof
Architecture: amd64
Version: 0.4.7-1build2
Priority: extra
Section: universe/haskell
Source: haskell-hierarchical-clustering
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Haskell Group
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 610
Provides: libghc-hierarchical-clustering-prof-0.4.7-1bc71
Depends: libghc-hierarchical-clustering-dev (= 0.4.7-1build2), libghc-array-prof-0.5.4.0-ddbb2, libghc-base-prof-4.13.0.0-2f220, libghc-containers-prof-0.6.2.1-ab1cf
Filename: pool/universe/h/haskell-hierarchical-clustering/libghc-hierarchical-clustering-prof_0.4.7-1build2_amd64.deb
Size: 71208
MD5sum: 28e2b496143ee95d3f1b7cb44f38793d
SHA1: bac21a127a9c8736146a9311382c9f152ef6e09f
SHA256: cbf343f80254a4c962d0a5a347770546601119c799552295332051819345986b
SHA512: ff1d7dd1b3b0c94d3cf2104a3efd2b0f6f9c51f8b6a85a954c7fe0d7500157ed143994b66acf0b33f64bf9b2e90a64d473733c7407a61d973376a78d9369a7f8
Homepage: https://hackage.haskell.org/package/hierarchical-clustering
Description-en: 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.
Description-md5: 2ed7496693bb612eee3b8d45d5f19334
Architecture: amd64
Version: 0.4.7-1build2
Priority: extra
Section: universe/haskell
Source: haskell-hierarchical-clustering
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Haskell Group
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 610
Provides: libghc-hierarchical-clustering-prof-0.4.7-1bc71
Depends: libghc-hierarchical-clustering-dev (= 0.4.7-1build2), libghc-array-prof-0.5.4.0-ddbb2, libghc-base-prof-4.13.0.0-2f220, libghc-containers-prof-0.6.2.1-ab1cf
Filename: pool/universe/h/haskell-hierarchical-clustering/libghc-hierarchical-clustering-prof_0.4.7-1build2_amd64.deb
Size: 71208
MD5sum: 28e2b496143ee95d3f1b7cb44f38793d
SHA1: bac21a127a9c8736146a9311382c9f152ef6e09f
SHA256: cbf343f80254a4c962d0a5a347770546601119c799552295332051819345986b
SHA512: ff1d7dd1b3b0c94d3cf2104a3efd2b0f6f9c51f8b6a85a954c7fe0d7500157ed143994b66acf0b33f64bf9b2e90a64d473733c7407a61d973376a78d9369a7f8
Homepage: https://hackage.haskell.org/package/hierarchical-clustering
Description-en: 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.
Description-md5: 2ed7496693bb612eee3b8d45d5f19334