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
