[jira] [Resolved] (SPARK-18678) Skewed reservoir sampling in SamplingUtils

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-18678?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-18678.
-------------------------------
       Resolution: Fixed
    Fix Version/s: 2.1.0

Resolved by https://github.com/apache/spark/pull/16129

> 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
>            Assignee: Sean Owen
>             Fix For: 2.1.0
>
>
> 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.



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