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https://issues.apache.org/jira/browse/SPARK-24609?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen updated SPARK-24609:
------------------------------
      Priority: Minor  (was: Major)
    Issue Type: Improvement  (was: Bug)

> PySpark/SparkR doc doesn't explain 
> RandomForestClassifier.featureSubsetStrategy well
> ------------------------------------------------------------------------------------
>
>                 Key: SPARK-24609
>                 URL: https://issues.apache.org/jira/browse/SPARK-24609
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark
>    Affects Versions: 2.3.1
>            Reporter: Xiangrui Meng
>            Assignee: zhengruifeng
>            Priority: Minor
>             Fix For: 2.4.0
>
>
> In Scala doc 
> ([https://spark.apache.org/docs/2.3.0/api/scala/index.html#org.apache.spark.ml.classification.RandomForestClassifier)],
>  we have:
>  
> {quote}The number of features to consider for splits at each tree node. 
> Supported options:
>  * "auto": Choose automatically for task: If numTrees == 1, set to "all." If 
> numTrees > 1 (forest), set to "sqrt" for classification and to "onethird" for 
> regression.
>  * "all": use all features
>  * "onethird": use 1/3 of the features
>  * "sqrt": use sqrt(number of features)
>  * "log2": use log2(number of features)
>  * "n": when n is in the range (0, 1.0], use n * number of features. When n 
> is in the range (1, number of features), use n features. (default = "auto")
> These various settings are based on the following references:
>  * log2: tested in Breiman (2001)
>  * sqrt: recommended by Breiman manual for random forests
>  * The defaults of sqrt (classification) and onethird (regression) match the 
> R randomForest package.{quote}
>  
> The entire paragraph is missing in PySpark doc 
> ([https://spark.apache.org/docs/2.3.0/api/python/pyspark.ml.html#pyspark.ml.classification.RandomForestClassifier.featureSubsetStrategy]).
>  And same issue for SparkR 
> (https://github.com/apache/spark/blob/master/R/pkg/R/mllib_tree.R#L365).



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