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Yan Facai (颜发才) edited comment on SPARK-20199 at 4/26/17 6:11 AM: ------------------------------------------------------------------ The work is easy, however **public method** is added and some adjustments are needed in inner implementation. Hence, I suggest to delay it until at least one of Committers agree to shepherd the issue. I have two questions: 1. For both GBDT and RandomForest share the attribute, we can pull `featureSubsetStrategy` parameter up to either TreeEnsembleParams or DecisionTreeParams. Which one is appropriate? 2. Is it right to add new parameter `featureSubsetStrategy` to Strategy class? Or add it to DecisionTree's train method? was (Author: facai): The work is easy, however Public method is added and some adjustments are needed in inner implementation. Hence, I suggest to delay it until one expert agree to shepherd the issue. I have two questions: 1. For both GBDT and RandomForest share the attribute, we can pull `featureSubsetStrategy` parameter up to either TreeEnsembleParams or DecisionTreeParams. Which one is appropriate? 2. Is it right to add new parameter `featureSubsetStrategy` to Strategy class? Or add it to DecisionTree's train method? > GradientBoostedTreesModel doesn't have Column Sampling Rate Paramenter > ----------------------------------------------------------------------- > > Key: SPARK-20199 > URL: https://issues.apache.org/jira/browse/SPARK-20199 > Project: Spark > Issue Type: Improvement > Components: ML, MLlib > Affects Versions: 2.1.0 > Reporter: pralabhkumar > > Spark GradientBoostedTreesModel doesn't have Column sampling rate parameter > . This parameter is available in H2O and XGBoost. > Sample from H2O.ai > gbmParams._col_sample_rate > Please provide the parameter . -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org