Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/15913#discussion_r89591662
--- Diff: mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala ---
@@ -317,8 +317,32 @@ private[ml] trait TreeEnsembleParams extends
DecisionTreeParams {
}
}
-/** Used for [[RandomForestParams]] */
-private[ml] trait HasFeatureSubsetStrategy extends Params {
+/**
+ * Parameters for Random Forest algorithms.
+ */
+private[ml] trait RandomForestParams extends TreeEnsembleParams {
+
+ /**
+ * Number of trees to train (>= 1).
+ * If 1, then no bootstrapping is used. If > 1, then bootstrapping is
done.
+ * TODO: Change to always do bootstrapping (simpler). SPARK-7130
+ * (default = 20)
+ *
+ * Note: The reason that we cannot add this to both GBT and RF (i.e. in
TreeEnsembleParams)
+ * is the param `maxIter` controls how many trees a GBT has. The
semantics in the algorithms
+ * are a bit different.
+ * @group param
+ */
+ final val numTrees: IntParam = new IntParam(this, "numTrees", "Number of
trees to train (>= 1)",
+ ParamValidators.gtEq(1))
+
+ setDefault(numTrees -> 20)
+
+ /** @group setParam */
+ def setNumTrees(value: Int): this.type = set(numTrees, value)
--- End diff --
Yeah, we already have ```setNumTrees``` which calls ```super.setNumTrees```
in ```RandomForestClassifier``` and ```RandomForestRegressor```.
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