[GitHub] [spark] zhengruifeng commented on pull request #31163: [SPARK-34093][ML] param maxDepth should check upper bound

[GitBox <gi...@apache.org>]

zhengruifeng commented on pull request #31163:
URL: https://github.com/apache/spark/pull/31163#issuecomment-759185176


   ```
   
   scala> import org.apache.spark.ml.classification._
   import org.apache.spark.ml.classification._
   
   scala> 
   
   scala> val df = spark.read.format("libsvm").load("/d0/Dev/Opensource/spark/data/mllib/sample_multiclass_classification_data.txt")
   21/01/13 11:40:35 WARN LibSVMFileFormat: 'numFeatures' option not specified, determining the number of features by going though the input. If you know the number in advance, please specify it via 'numFeatures' option to avoid the extra scan.
   df: org.apache.spark.sql.DataFrame = [label: double, features: vector]
   
   scala> val dt = new DecisionTreeClassifi
   DecisionTreeClassificationModel   DecisionTreeClassifier
   
   scala> val dt = new DecisionTreeClassifier().setMax
   setMaxBins   setMaxDepth   setMaxMemoryInMB
   
   scala> val dt = new DecisionTreeClassifier().setMaxDepth(32)
   dt: org.apache.spark.ml.classification.DecisionTreeClassifier = dtc_9ad3d8b78d64
   
   scala> dt.fit(df)
   21/01/13 11:41:01 ERROR Instrumentation: java.lang.IllegalArgumentException: requirement failed: DecisionTree currently only supports maxDepth <= 30, but was given maxDepth = 32.
   	at scala.Predef$.require(Predef.scala:281)
   	at org.apache.spark.ml.tree.impl.RandomForest$.runBagged(RandomForest.scala:145)
   	at org.apache.spark.ml.tree.impl.RandomForest$.run(RandomForest.scala:302)
   	at org.apache.spark.ml.classification.DecisionTreeClassifier.$anonfun$train$1(DecisionTreeClassifier.scala:135)
   	at org.apache.spark.ml.util.Instrumentation$.$anonfun$instrumented$1(Instrumentation.scala:191)
   	at scala.util.Try$.apply(Try.scala:213)
   	at org.apache.spark.ml.util.Instrumentation$.instrumented(Instrumentation.scala:191)
   	at org.apache.spark.ml.classification.DecisionTreeClassifier.train(DecisionTreeClassifier.scala:114)
   	at org.apache.spark.ml.classification.DecisionTreeClassifier.train(DecisionTreeClassifier.scala:46)
   	at org.apache.spark.ml.Predictor.fit(Predictor.scala:150)
   	at $line21.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:31)
   	at $line21.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:35)
   
   
   ```


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