Apache Mahout has reached version 0.6. All developers are encouraged to
begin using version 0.6, as much has changed and will continue to do so
as we march inexorably toward a 1.0 release. Highlights of 0.6 include:
-Improved Decision Tree performance and added support for regression
problems
-New LDA implementation using Collapsed Variational Bayes 0th Derivative
Approximation
-Reduced runtime of LanczosSolver tests
-K-Trusses, Top-Down and Bottom-Up clustering, Random Walk with Restarts
implementation
-Reduced runtime of dot product between vectors
-Added MongoDB and Cassandra DataModel support
-Increased efficiency of parallel ALS matrix factorization
-SSVD enhancements
-Performance improvements in RowSimilarityJob, TransposeJob
-Added numerous clustering display examples
-Many bug fixes, refactorings, and other small improvements
Changes in 0.6 are detailed in the release notes (
https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12310751&version=12316364
<https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12310751&version=12316364>).
Downloads of all releases available from Apache mirrors. (
http://www.apache.org/dyn/closer.cgi/mahout/
<http://www.apache.org/dyn/closer.cgi/mahout/>)
Enjoy!
Regards,
Shannon
