Move experimental annotation to the top of the docstrings

Author: zero323

python/pyspark/ml/fpm.py

@@ -95,10 +95,11 @@ def getItemsCol(self):
 
 
 class FPGrowthModel(JavaModel, JavaMLWritable, JavaMLReadable):
-    """Model fitted by FPGrowth.
-
+    """
     .. note:: Experimental
 
+    Model fitted by FPGrowth.
+
     .. versionadded:: 2.2.0
     """
     @property
@@ -125,7 +126,10 @@ def associationRules(self):
 
 class FPGrowth(JavaEstimator, HasItemsCol, HasPredictionCol,
                HasSupport, HasConfidence, JavaMLWritable, JavaMLReadable):
-    """A parallel FP-growth algorithm to mine frequent itemsets. The algorithm is described in
+    """
+    .. note:: Experimental
+
+    A parallel FP-growth algorithm to mine frequent itemsets. The algorithm is described in
     Li et al., PFP: Parallel FP-Growth for Query Recommendation [LI2008]_.
     PFP distributes computation in such a way that each worker executes an
     independent group of mining tasks. The FP-Growth algorithm is described in
@@ -134,7 +138,6 @@ class FPGrowth(JavaEstimator, HasItemsCol, HasPredictionCol,
     .. [LI2008] http://dx.doi.org/10.1145/1454008.1454027
     .. [HAN2000] http://dx.doi.org/10.1145/335191.335372
 
-    .. note:: Experimental
     .. note:: null values in the feature column are ignored during fit().
     .. note:: Internally `transform` `collects` and `broadcasts` association rules.
 
@@ -181,8 +184,6 @@ class FPGrowth(JavaEstimator, HasItemsCol, HasPredictionCol,
     >>> sorted(fpm.transform(new_data).first().prediction)
     ['x', 'y', 'z']
 
-    .. note:: Experimental
-
     .. versionadded:: 2.2.0
     """
     @keyword_only