Karen Yin-Yee Ng created SPARK-10578: ----------------------------------------
Summary: pyspark.ml.classification.RandomForestClassifer does not return `rawPrediction` column Key: SPARK-10578 URL: https://issues.apache.org/jira/browse/SPARK-10578 Project: Spark Issue Type: Bug Components: ML Affects Versions: 1.4.1, 1.4.0 Environment: CentOS, PySpark 1.4.1, Scala 2.10 Reporter: Karen Yin-Yee Ng To use `pyspark.ml.classification.RandomForestClassifer` with `BinaryClassificationEvaluator`, a column called `rawPrediction` needs to be returned by the `RandomForestClassifer`. The PySpark documentation example of `logisticsRegression`outputs the `rawPrediction` column but not `RandomForestClassifier`. Therefore, one is unable to use `RandomForestClassifier` with the evaluator nor put it in a pipeline with cross validation. A relevant piece of code showing how to reproduce the bug can be found at: https://gist.github.com/karenyyng/cf61ae655b032f754bfb A relevant post due to this possible bug can also be found at: http://apache-spark-user-list.1001560.n3.nabble.com/Issue-with-running-CrossValidator-with-RandomForestClassifier-on-dataset-td23791.html -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org