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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