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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 reassigned SPARK-24609:
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Assignee: zhengruifeng
> 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: Bug
> Components: PySpark
> Affects Versions: 2.3.1
> Reporter: Xiangrui Meng
> Assignee: zhengruifeng
> Priority: Major
> 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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