Hi, The paper compares the performance between your XGBoost and the Spark MLlib version. It would be nice to see how it scales when using Spark or Flink as an engine and also compare it to your native distributed version (with rabit, right?).
If you have some charts, they are welcome :-) BTW, where did you submit this paper (if not confidential of course)? Thanks! Christophe 2016-03-15 0:41 GMT+01:00 Tianqi Chen <tqc...@cs.washington.edu>: > Hi Flink Community: > I am sending this email to let you know we just release XGBoost4J > which also runs on Flink. In short, XGBoost is a machine learning package > that is used by more than half of the machine challenge winning solutions > and is already widely used in industry. The distributed version scale to > billion examples(10x faster than spark.mllib in the experiment) with fewer > resources (see .http://arxiv.org/abs/1603.02754) > > See our blogpost for more details > http://dmlc.ml/2016/03/14/xgboost4j-portable-distributed-xgboost-in-spark-flink-and-dataflow.html > We > would love to have you try it out and helo us to make it better. > > Cheers >
