Doc of Java updated. algo -> algoStr instead.

jkbradley · Jan 21, 2015 · 7c1e6ee · 7c1e6ee
1 parent d5c8a2e
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diff --git a/docs/mllib-ensembles.md b/docs/mllib-ensembles.md
@@ -506,7 +506,7 @@ JavaRDD<LabeledPoint> testData = splits[1];
 
 // Train a GradientBoostedTrees model.
 //  The defaultParams for Classification use LogLoss by default.
-BoostingStrategy boostingStrategy = BoostingStrategy.defaultParams(Algo.Classification);
+BoostingStrategy boostingStrategy = BoostingStrategy.defaultParams(Algo.Classification());
 boostingStrategy.setNumIterations(3); // Note: Use more iterations in practice.
 boostingStrategy.getTreeStrategy().setNumClassesForClassification(2);
 boostingStrategy.getTreeStrategy().setMaxDepth(5);
@@ -614,7 +614,7 @@ JavaRDD<LabeledPoint> testData = splits[1];
 
 // Train a GradientBoostedTrees model.
 //  The defaultParams for Regression use SquaredError by default.
-BoostingStrategy boostingStrategy = BoostingStrategy.defaultParams(Algo.Regression);
+BoostingStrategy boostingStrategy = BoostingStrategy.defaultParams(Algo.Regression());
 boostingStrategy.setNumIterations(3); // Note: Use more iterations in practice.
 boostingStrategy.getTreeStrategy().setMaxDepth(5);
 //  Empty categoricalFeaturesInfo indicates all features are continuous.

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/BoostingStrategy.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/BoostingStrategy.scala
@@ -70,22 +70,22 @@ object BoostingStrategy {
 
   /**
    * Returns default configuration for the boosting algorithm
-   * @param algo Learning goal.  Supported:
+   * @param algoStr Learning goal.  Supported:
    *             [[org.apache.spark.mllib.tree.configuration.Algo.Classification]],
    *             [[org.apache.spark.mllib.tree.configuration.Algo.Regression]]
    * @return Configuration for boosting algorithm
    */
-  def defaultParams(algo: String): BoostingStrategy = {
-    val treeStrategy = Strategy.defaultStrategy(algo)
+  def defaultParams(algoStr: String): BoostingStrategy = {
+    val treeStrategy = Strategy.defaultStrategy(algoStr)
     treeStrategy.maxDepth = 3
-    algo match {
+    algoStr match {
       case "Classification" =>
         treeStrategy.numClasses = 2
         new BoostingStrategy(treeStrategy, LogLoss)
       case "Regression" =>
         new BoostingStrategy(treeStrategy, SquaredError)
       case _ =>
-        throw new IllegalArgumentException(s"$algo is not supported by boosting.")
+        throw new IllegalArgumentException(s"$algoStr is not supported by boosting.")
     }
   }
 

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala
@@ -171,9 +171,9 @@ object Strategy {
 
   /**
    * Construct a default set of parameters for [[org.apache.spark.mllib.tree.DecisionTree]]
-   * @param algo  "Classification" or "Regression"
+   * @param algoStr  "Classification" or "Regression"
    */
-  def defaultStrategy(algo: String): Strategy = algo match {
+  def defaultStrategy(algoStr: String): Strategy = algoStr match {
     case "Classification" =>
       new Strategy(algo = Classification, impurity = Gini, maxDepth = 10,
         numClasses = 2)