[SPARK-18447][DOCS] Fix the markdown for `Note:`/`NOTE:`/`Note that` across Python API documentation

## What changes were proposed in this pull request?

It seems in Python, there are

- `Note:`
- `NOTE:`
- `Note that`
- `.. note::`

This PR proposes to fix those to `.. note::` to be consistent.

**Before**

<img width="567" alt="2016-11-21 1 18 49" src="https://cloud.githubusercontent.com/assets/6477701/20464305/85144c86-af88-11e6-8ee9-90f584dd856c.png">

<img width="617" alt="2016-11-21 12 42 43" src="https://cloud.githubusercontent.com/assets/6477701/20464263/27be5022-af88-11e6-8577-4bbca7cdf36c.png">

**After**

<img width="554" alt="2016-11-21 1 18 42" src="https://cloud.githubusercontent.com/assets/6477701/20464306/8fe48932-af88-11e6-83e1-fc3cbf74407d.png">

<img width="628" alt="2016-11-21 12 42 51" src="https://cloud.githubusercontent.com/assets/6477701/20464264/2d3e156e-af88-11e6-93f3-cab8d8d02983.png">

## How was this patch tested?

The notes were found via

```bash
grep -r "Note: " .
grep -r "NOTE: " .
grep -r "Note that " .
```

And then fixed one by one comparing with API documentation.

After that, manually tested via `make html` under `./python/docs`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15947 from HyukjinKwon/SPARK-18447.

1 files changed, 7 insertions, 6 deletions

diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 635cf13045..40b63d4d31 100755
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -742,8 +742,8 @@ class MinMaxScaler(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, Jav
 
     For the case E_max == E_min, Rescaled(e_i) = 0.5 * (max + min)
 
-    Note that since zero values will probably be transformed to non-zero values, output of the
-    transformer will be DenseVector even for sparse input.
+    .. note:: Since zero values will probably be transformed to non-zero values, output of the
+        transformer will be DenseVector even for sparse input.
 
     >>> from pyspark.ml.linalg import Vectors
     >>> df = spark.createDataFrame([(Vectors.dense([0.0]),), (Vectors.dense([2.0]),)], ["a"])
@@ -1014,9 +1014,9 @@ class OneHotEncoder(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
     :py:attr:`dropLast`) because it makes the vector entries sum up to
     one, and hence linearly dependent.
     So an input value of 4.0 maps to `[0.0, 0.0, 0.0, 0.0]`.
-    Note that this is different from scikit-learn's OneHotEncoder,
-    which keeps all categories.
-    The output vectors are sparse.
+
+    .. note:: This is different from scikit-learn's OneHotEncoder,
+        which keeps all categories. The output vectors are sparse.
 
     .. seealso::
 
@@ -1698,7 +1698,8 @@ class IndexToString(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
 class StopWordsRemover(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWritable):
     """
     A feature transformer that filters out stop words from input.
-    Note: null values from input array are preserved unless adding null to stopWords explicitly.
+
+    .. note:: null values from input array are preserved unless adding null to stopWords explicitly.
 
     >>> df = spark.createDataFrame([(["a", "b", "c"],)], ["text"])
     >>> remover = StopWordsRemover(inputCol="text", outputCol="words", stopWords=["b"])