Fedora 22 Update: mlpack-1.0.11-11.fc22

[updates at fedoraproject.org]

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Fedora Update Notification
FEDORA-2016-de7dbf080e
2016-03-05 18:25:11.095000
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Name        : mlpack
Product     : Fedora 22
Version     : 1.0.11
Release     : 11.fc22
URL         : http://www.mlpack.org
Summary     : Scalable, fast C++ machine learning library
Description :
mlpack is a C++ machine learning library with emphasis on scalability, speed,
and ease-of-use. Its aim is to make machine learning possible for novice users
by means of a simple, consistent API, while simultaneously exploiting C++
language features to provide maximum performance and maximum flexibility for
expert users. mlpack outperforms competing machine learning libraries by large
margins.

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Update Information:

Update armadillo to the supported stable release.  Changes since version (5.600)
* correction for datum::Z_0 constant * fixes for corner cases in gmm_diag class
* fixes for spsolve(), eigs_sym(), eigs_gen(), svds() * advanced constructors
for using auxiliary memory now have the default of strict = false * Cube class
now delays allocation of .slice() related structures until needed * stricter
handling of matrix objects by hist() and histc() * added conv2() for 2D
convolution * added stand-alone kmeans() function for clustering data * added
trunc() * added ind2sub() and sub2ind() * added .for_each() to Mat, Row, Col,
Cube and field classes * added rcond() for estimating the reciprocal condition
number * added Schur decomposition: schur() * expanded solve() to find
approximate solutions for rank-deficient systems * expanded join_slices() to
handle joining cubes with matrices* faster handling of non-contiguous submatrix
views in compound expressions * expanded each_col(), each_row() and each_slice()
to handle C++11 lambda functions * expanded diagmat() to handle non-square
matrices and arbitrary diagonals * expanded trace() to handle non-square
matrices * extended conv() to optionally provide central convolution * faster
handling of multiply-and-accumulate by accu() when using Intel MKL, ATLAS or
OpenBLAS * faster norm() and normalise() when using Intel MKL, ATLAS or OpenBLAS
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References:

  [ 1 ] Bug #1268277 - armadillo-6.500.5 is available
        https://bugzilla.redhat.com/show_bug.cgi?id=1268277
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This update can be installed with the "yum" update program. Use
su -c 'yum update mlpack' at the command line.
For more information, refer to "Managing Software with yum",
available at https://docs.fedoraproject.org/yum/.

All packages are signed with the Fedora Project GPG key.  More details on the
GPG keys used by the Fedora Project can be found at
https://fedoraproject.org/keys
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