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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). -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org