Github user BryanCutler commented on the issue:
https://github.com/apache/spark/pull/15113
Hi @yanboliang , thanks for taking a look!
I'm more inclined to think that most Python users would think that
`weightCol=None` does not cause a problem, as in this corresponding JIRA. Most
are unaware that Py4J will convert the value to `null` behind the scenes. Let
me show the LogisticRegression constructor as an example
```
@keyword_only
def __init__(self, featuresCol="features", labelCol="label",
predictionCol="prediction",
maxIter=100, regParam=0.0, elasticNetParam=0.0, tol=1e-6,
fitIntercept=True,
threshold=0.5, thresholds=None,
probabilityCol="probability",
rawPredictionCol="rawPrediction", standardization=True,
weightCol=None,
aggregationDepth=2):
```
Here it shows `maxIter=100` which means that the param `maxIter` has a
default value of 100. Then it shows `weightCol=None`, but this does not mean
that `weightCol` has a default value of `null`, it means that the param
`weightCol` is not set by default. So why would it have a different effect if
the user explicitly writes it?
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