[Announce] Apache MADlib v1.13 released

[Ed Espino <es...@apache.org>]

The Apache MADlib team is pleased to announce the immediate
availability of the 1.13 release.

The main goals of this release are:

New features:

* New module: Graph - HITS (MADLIB-1124, MADLIB-1151)
* k-NN:
  - Added additional distance metrics (MADLIB-1059)
  - Added list of neighbors in output table (MADLIB-1129)
* MLP: Added grouping support (MADLIB-1149)
* Cross Validation: Improved the stats reporting in output table
  (MADLIB-1169)
* Correlation: Improved quality of results by ignoring only a NULL
  value and not the whole row containing the NULL (MADLIB-1166)

Bug fixes:

  - Fixed issue with Decision Trees (DT) trained in older versions not
    being usable in predict of v1.12 (MADLIB-1161)
  - Fixed invalid assert statement in DT (MADLIB-1164)
  - Improved feature array handling in DT (MADLIB-1173)
  - Fixed install-check failures on non-default schema installation
    (MADLIB-1177, 1184)

Other:
  - Updated PyXB from 1.2.4 to 1.2.6. (MADLIB-1103)
    This change eliminates the need to remove part of PyXB codebase as
    a GPL-workaround.
  - Updated the naming for gppkg (MADLIB-1183)

All release changes can be found here:

  https://cwiki.apache.org/confluence/display/MADLIB/MADlib+1.13

You can download the source release and convenience binary packages
from Apache MADlib's download page here:

  http://madlib.apache.org/download.html

Alternatively, you can download through an ASF mirror near you:

  https://www.apache.org/dyn/closer.lua/madlib/1.13

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Apache MADlib is an open-source library for scalable in-database
analytics. It provides data-parallel implementations of mathematical,
statistical and machine learning methods for structured and
unstructured data.

The MADlib mission: to foster widespread development of scalable
analytic skills, by harnessing efforts from commercial practice,
academic research, and open-source development.

We welcome your help and feedback. For more information on how to
report problems, and to get involved, visit the project website at
https://madlib.apache.org

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Thank you, everyone who contributed to the MADlib 1.13 release. We
look forward to continued community participation for the next
release.

Regards,
Your Apache MADlib team