Hello all, We have released a newer version of Hivemall, v0.3-beta2.
Hivemall is an open-source implementation of a scalable machine learning that runs on Hive/Hadoop. https://github.com/myui/hivemall http://bit.ly/hivemall-hadoopsummit14 (slide at Hadoop Summit'14) Hivemall is easy to use if you have a Hive environment because every machine learning step is done within HiveQL. In the latest release (v0.3), we have supported the following state of the art convex optimization algorithms (please refer the project site for the complete list of supported algorithms): o AdaGrad o AdaGradRDA o AdaDelta Moreover, Hivemall v0.3 now supports parameter mixing for better stable/prediction performance and fast convergence of a learning process. https://github.com/myui/hivemall/wiki/How-to-use-Model-Mixing With the MIX protocol, distributed learners (run as distinct Hadoop tasks) communicate with each other by using an external communication support service. By using the MIX protocol (and Hivemall's amplifier method), iterations are no more mandatory and machine learning perfectly runs on the plain Hadoop/Hive. Hivemall runs on Tez as well. Hope you enjoy the release! Feedback and pull requests are welcome. Thanks, Makoto