[jira] [Created] (SPARK-18036) Decision Trees do not handle edge cases

["Seth Hendrickson (JIRA)" <ji...@apache.org>]

Seth Hendrickson created SPARK-18036:
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             Summary: Decision Trees do not handle edge cases
                 Key: SPARK-18036
                 URL: https://issues.apache.org/jira/browse/SPARK-18036
             Project: Spark
          Issue Type: Bug
          Components: ML, MLlib
            Reporter: Seth Hendrickson
            Priority: Minor


Decision trees/GBT/RF do not handle edge cases such as constant features or empty features. For example:

{code}
val dt = new DecisionTreeRegressor()
val data = Seq(LabeledPoint(1.0, Vectors.dense(Array.empty[Double]))).toDF()
dt.fit(data)

java.lang.UnsupportedOperationException: empty.max
  at scala.collection.TraversableOnce$class.max(TraversableOnce.scala:229)
  at scala.collection.mutable.ArrayOps$ofInt.max(ArrayOps.scala:234)
  at org.apache.spark.ml.tree.impl.DecisionTreeMetadata$.buildMetadata(DecisionTreeMetadata.scala:207)
  at org.apache.spark.ml.tree.impl.RandomForest$.run(RandomForest.scala:105)
  at org.apache.spark.ml.regression.DecisionTreeRegressor.train(DecisionTreeRegressor.scala:93)
  at org.apache.spark.ml.regression.DecisionTreeRegressor.train(DecisionTreeRegressor.scala:46)
  at org.apache.spark.ml.Predictor.fit(Predictor.scala:90)
  ... 52 elided

{code}

as well as 

{code}
val dt = new DecisionTreeRegressor()
val data = Seq(LabeledPoint(1.0, Vectors.dense(0.0, 0.0, 0.0))).toDF()
dt.fit(data)

java.lang.UnsupportedOperationException: empty.maxBy
at scala.collection.TraversableOnce$class.maxBy(TraversableOnce.scala:236)
at scala.collection.SeqViewLike$AbstractTransformed.maxBy(SeqViewLike.scala:37)
at org.apache.spark.ml.tree.impl.RandomForest$.binsToBestSplit(RandomForest.scala:846)
{code}



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