r-cran-fastcluster 1.1.16-2 source package in Ubuntu


r-cran-fastcluster (1.1.16-2) unstable; urgency=medium

  * Create Python modules as well (Thanks for the hint to Gard Spreemann
    <email address hidden>)
    Closes:  #808743

 -- Andreas Tille <email address hidden>  Sun, 24 Jan 2016 19:05:45 +0100

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Uploaded by:
Debian Med on 2016-01-29
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Original maintainer:
Debian Med
Medium Urgency

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Series Pocket Published Component Section
Xenial release on 2016-02-15 universe misc


File Size SHA-256 Checksum
r-cran-fastcluster_1.1.16-2.dsc 2.3 KiB 49c064e752d852901897df9f9c48010f7d535a8a888ddd95c01bfdcf99db1d98
r-cran-fastcluster_1.1.16.orig.tar.gz 178.8 KiB 08071e7088386f45e200471b78510108cb669f12dec43944c7b1446c75ce5774
r-cran-fastcluster_1.1.16-2.debian.tar.xz 3.8 KiB 8476127ae24b71b4d3f681e3d6a8863bcf1fdd325727459a350dbb0fe4b5712b

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python-fastcluster: No summary available for python-fastcluster in ubuntu yakkety.

No description available for python-fastcluster in ubuntu yakkety.

python3-fastcluster: Fast hierarchical clustering routines for Python 3

 This library provides Python functions for hierarchical
 clustering. It generates hierarchical clusters from distance matrices
 or from vector data.
 Part of this module is intended to replace the functions
     linkage, single, complete, average, weighted, centroid, median, ward
 in the module scipy.cluster.hierarchy with the same functionality but
 much faster algorithms. Moreover, the function 'linkage_vector'
 provides memory-efficient clustering for vector data.
 The interface is very similar to MATLAB's Statistics Toolbox API to
 make code easier to port from MATLAB to Python/Numpy. The core
 implementation of this library is in C++ for efficiency.
 This package provides the package's Python 3 interface.

r-cran-fastcluster: No summary available for r-cran-fastcluster in ubuntu zesty.

No description available for r-cran-fastcluster in ubuntu zesty.

r-cran-fastcluster-dbgsym: debug symbols for package r-cran-fastcluster

 Fastcluster implements fast hierarchical, agglomerative clustering
 routines. Part of the functionality is designed as drop-in replacement
 for existing routines: “linkage” in the SciPy package
 “scipy.cluster.hierarchy”, “hclust” in R's “stats” package, and the
 “flashClust” package. It provides the same functionality with the
 benefit of a much faster implementation. Moreover, there are
 memory-saving routines for clustering of vector data, which go beyond
 what the existing packages provide. For information on how to install
 the Python files, see the file INSTALL in the source distribution.