[GitHub] srowen commented on a change in pull request #23818: [SPARK-19591][ML][PYSPARK][FOLLOWUP] Add sample weights to decision trees

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srowen commented on a change in pull request #23818: [SPARK-19591][ML][PYSPARK][FOLLOWUP] Add sample weights to decision trees
URL: https://github.com/apache/spark/pull/23818#discussion_r258577213
 
 

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 File path: python/pyspark/ml/classification.py
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 @@ -902,12 +902,12 @@ class DecisionTreeClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPred
     >>> from pyspark.ml.linalg import Vectors
     >>> from pyspark.ml.feature import StringIndexer
     >>> df = spark.createDataFrame([
-    ...     (1.0, Vectors.dense(1.0)),
-    ...     (0.0, Vectors.sparse(1, [], []))], ["label", "features"])
+    ...     (1.0, 1.0, Vectors.dense(1.0)),
 
 Review comment:
   My only nit here is that now this shows usage with weights, only, but the weight is 1. Maybe have two quick examples, one without specifying weight and one with a weight != 1?

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