GitHub user smurching opened a pull request: https://github.com/apache/spark/pull/14872
Add local tree training for decision tree regressors ## What changes were proposed in this pull request? Based on [Yggdrasil](https://github.com/fabuzaid21/yggdrasil), added local training of decision tree regressors. Some classes/objects largely correspond to Yggdrasil classes/objects. Specifically: * class LocalDecisionTreeRegressor --> class YggdrasilRegressor * object LocalDecisionTree --> object YggdrasilRegression * object LocalDecisionTreeUtils --> object Yggdrasil ## How was this patch tested? Added unit tests in (ml/tree/impl/LocalTreeTrainingSuite.scala) verifying that local & distributed training of a decision tree regressor produces the same tree. You can merge this pull request into a Git repository by running: $ git pull https://github.com/smurching/spark local-trees-pr Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/14872.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #14872 ---- commit acf5b3e29a346a0cb86f621269855a6a98a9a74e Author: Siddharth Murching <smurch...@databricks.com> Date: 2016-08-29T23:51:33Z Add local tree training for decision tree regressors commit aa4fcc8d401385f38fe0cdfdb9fe39062c3a9f96 Author: Siddharth Murching <smurch...@databricks.com> Date: 2016-08-30T01:19:07Z Fix setting of impurity values for leaf nodes to match values produced by distributed Random Forest algorithm ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org