There's an xgboost exploration jira SPARK-8547. Can it be a good start? 2015-10-27 7:07 GMT+08:00 DB Tsai <dbt...@dbtsai.com>: > Also, does it support categorical feature? > > Sincerely, > > DB Tsai > ---------------------------------------------------------- > Web: https://www.dbtsai.com > PGP Key ID: 0xAF08DF8D > > > On Mon, Oct 26, 2015 at 4:06 PM, DB Tsai <dbt...@dbtsai.com> wrote: >> Interesting. For feature sub-sampling, is it per-node or per-tree? Do >> you think you can implement generic GBM and have it merged as part of >> Spark codebase? >> >> Sincerely, >> >> DB Tsai >> ---------------------------------------------------------- >> Web: https://www.dbtsai.com >> PGP Key ID: 0xAF08DF8D >> >> >> On Mon, Oct 26, 2015 at 11:42 AM, Meihua Wu >> <rotationsymmetr...@gmail.com> wrote: >>> Hi Spark User/Dev, >>> >>> Inspired by the success of XGBoost, I have created a Spark package for >>> gradient boosting tree with 2nd order approximation of arbitrary >>> user-defined loss functions. >>> >>> https://github.com/rotationsymmetry/SparkXGBoost >>> >>> Currently linear (normal) regression, binary classification, Poisson >>> regression are supported. You can extend with other loss function as >>> well. >>> >>> L1, L2, bagging, feature sub-sampling are also employed to avoid >>> overfitting. >>> >>> Thank you for testing. I am looking forward to your comments and >>> suggestions. Bugs or improvements can be reported through GitHub. >>> >>> Many thanks! >>> >>> Meihua >>> >>> --------------------------------------------------------------------- >>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>> For additional commands, e-mail: user-h...@spark.apache.org >>> > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org >
-- Yizhi Liu Senior Software Engineer / Data Mining www.mvad.com, Shanghai, China --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org For additional commands, e-mail: dev-h...@spark.apache.org
