Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/10469#discussion_r50902970
--- Diff: python/pyspark/ml/regression.py ---
@@ -68,6 +68,30 @@ class LinearRegression(JavaEstimator, HasFeaturesCol,
HasLabelCol, HasPrediction
Traceback (most recent call last):
...
TypeError: Method setParams forces keyword arguments.
+ >>> import os, tempfile
+ >>> path = tempfile.mkdtemp()
+ >>> lr_path = path + "/lr"
+ >>> lr.save(lr_path)
+ >>> lr2 = LinearRegression.load(lr_path)
+ >>> lr2.getOrDefault(lr2.getParam("maxIter"))
+ 5
+ >>> model2 = lr2.fit(df)
--- End diff --
Actually, I don't think you need to fit a second model. If the goal is to
test that all params are the same, that should be done explicitly in a unit
test (but it's OK with me not to).
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