[SPARK-14714][ML][PYTHON] Fixed issues with non-kwarg typeConverter arg for Param constructor

## What changes were proposed in this pull request?

PySpark Param constructors need to pass the TypeConverter argument by name, partly to make sure it is not mistaken for the expectedType arg and partly because we will remove the expectedType arg in 2.1. In several places, this is not being done correctly.

This PR changes all usages in pyspark/ml/ to keyword args.

## How was this patch tested?

Existing unit tests.  I will not test type conversion for every Param unless we really think it necessary.

Also, if you start the PySpark shell and import classes (e.g., pyspark.ml.feature.StandardScaler), then you no longer get this warning:
```
/Users/josephkb/spark/python/pyspark/ml/param/__init__.py:58: UserWarning: expectedType is deprecated and will be removed in 2.1. Use typeConverter instead, as a keyword argument.
  "Use typeConverter instead, as a keyword argument.")
```
That warning came from the typeConverter argument being passes as the expectedType arg by mistake.

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #12480 from jkbradley/typeconverter-fix.

1 files changed, 2 insertions, 1 deletions

diff --git a/python/pyspark/ml/clustering.py b/python/pyspark/ml/clustering.py
index 64c4bf1b92..05aa2dfe74 100644
--- a/python/pyspark/ml/clustering.py
+++ b/python/pyspark/ml/clustering.py
@@ -92,7 +92,8 @@ class KMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIter, HasTol
     initMode = Param(Params._dummy(), "initMode",
                      "the initialization algorithm. This can be either \"random\" to " +
                      "choose random points as initial cluster centers, or \"k-means||\" " +
-                     "to use a parallel variant of k-means++", TypeConverters.toString)
+                     "to use a parallel variant of k-means++",
+                     typeConverter=TypeConverters.toString)
     initSteps = Param(Params._dummy(), "initSteps", "steps for k-means initialization mode",
                       typeConverter=TypeConverters.toInt)