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Changes for 0.0.4 |
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This release focuses mostly on new features and bug fixing.
- Added experimental support for MariaDB / MySQL / MySQL Cluster. See Using DeepDive with MySQL for details, including limitations of the current support. The code base was refactored to make it much easier to add support for additional DBMS in the future.
- Ported Tuffy to DeepDive. It is now possible to run Tuffy programs for Markov Logic Networks on DeepDive. See Markov Logic Networks for details.
- Added a graphical interface called Mindtagger to label data products for
estimating precision/recall. See Labeling Data Products of
DeepDive and files under
examples/labeling/
in the source tree. - Added support for the
DEEPDIVE_HOME
environmental variable. It's now possible to run applications from any location, when this variable is set. See Installation for details. - Added support for
-c datacopies
to the DimmWitted sampler (Linux only!). This allows to control the number of replications of the data. It is useful for performing inference on very large factor graphs while leveraging on NUMA. See The DimmWitted High-Speed Sampler for details. - Fixed integer overflow bug (and use of scientific notation) in
tobinary.py
. This allows to use DeepDive for inference on very large factor graphs. - Fix a bug when using multinomial and GreenPlum: the mapping from weight ID and weight description is not consistent
- Fixed various bugs (including known JDBC bug) that prevented DeepDive from performing inference on very large factor graphs.