[ https://issues.apache.org/jira/browse/SPARK-18678?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen updated SPARK-18678: ------------------------------ Summary: Skewed reservoir sampling in SamplingUtils (was: Skewed feature subsampling in Random forest) > Skewed reservoir sampling in SamplingUtils > ------------------------------------------ > > Key: SPARK-18678 > URL: https://issues.apache.org/jira/browse/SPARK-18678 > Project: Spark > Issue Type: Bug > Components: ML > Affects Versions: 2.0.2 > Reporter: Bjoern Toldbod > > The feature subsampling performed in the RandomForest-implementation from > org.apache.spark.ml.tree.impl.RandomForest > is performed using SamplingUtils.reservoirSampleAndCount > The implementation of the sampling skews feature selection in favor of > features with a higher index. > The skewness is smaller for a large number of features, but completely > dominates the feature selection for a small number of features. The extreme > case is when the number of features is 2 and number of features to select is > 1. > In this case the feature sampling will always pick feature 1 and ignore > feature 0. > Of course this produces low quality models for few features when using > subsampling. -- 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