I'm curious about the state of development Multi-Model learning in MLlib (training sets of models during the same training session, rather then one at a time). The JIRA lists it as in progress targeting Spark 1.2.0 ( https://issues.apache.org/jira/browse/SPARK-1486 ). But there hasn't been any notes on it in over a month. I submitted a pull request for a possible method to do this work a little over two months ago (https://github.com/apache/spark/pull/1292), but haven't yet received any feedback on the patch yet. Is anybody else working on multi-model training?
Kyle
