[SPARK-18319][ML][QA2.1] 2.1 QA: API: Experimental, DeveloperApi, final, sealed audit

## What changes were proposed in this pull request?
make a pass through the items marked as Experimental or DeveloperApi and see if any are stable enough to be unmarked. Also check for items marked final or sealed to see if they are stable enough to be opened up as APIs.

Some discussions in the jira: https://issues.apache.org/jira/browse/SPARK-18319

## How was this patch tested?
existing ut

Author: Yuhao <yuhao.yang@intel.com>
Author: Yuhao Yang <hhbyyh@gmail.com>

Closes #15972 from hhbyyh/experimental21.

4 files changed, 0 insertions, 32 deletions

diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index 8054a34db3..5fe4bab186 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -1138,8 +1138,6 @@ class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol,
                                      HasMaxIter, HasTol, HasSeed, HasStepSize, JavaMLWritable,
                                      JavaMLReadable):
     """
-    .. note:: Experimental
-
     Classifier trainer based on the Multilayer Perceptron.
     Each layer has sigmoid activation function, output layer has softmax.
     Number of inputs has to be equal to the size of feature vectors.
@@ -1311,8 +1309,6 @@ class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol,
 class MultilayerPerceptronClassificationModel(JavaModel, JavaPredictionModel, JavaMLWritable,
                                               JavaMLReadable):
     """
-    .. note:: Experimental
-
     Model fitted by MultilayerPerceptronClassifier.
 
     .. versionadded:: 1.6.0
diff --git a/python/pyspark/ml/clustering.py b/python/pyspark/ml/clustering.py
index b29b5ac70e..7f8d845564 100644
--- a/python/pyspark/ml/clustering.py
+++ b/python/pyspark/ml/clustering.py
@@ -87,8 +87,6 @@ class ClusteringSummary(JavaWrapper):
 
 class GaussianMixtureModel(JavaModel, JavaMLWritable, JavaMLReadable):
     """
-    .. note:: Experimental
-
     Model fitted by GaussianMixture.
 
     .. versionadded:: 2.0.0
@@ -141,8 +139,6 @@ class GaussianMixtureModel(JavaModel, JavaMLWritable, JavaMLReadable):
 class GaussianMixture(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIter, HasTol, HasSeed,
                       HasProbabilityCol, JavaMLWritable, JavaMLReadable):
     """
-    .. note:: Experimental
-
     GaussianMixture clustering.
     This class performs expectation maximization for multivariate Gaussian
     Mixture Models (GMMs).  A GMM represents a composite distribution of
@@ -441,8 +437,6 @@ class KMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIter, HasTol
 
 class BisectingKMeansModel(JavaModel, JavaMLWritable, JavaMLReadable):
     """
-    .. note:: Experimental
-
     Model fitted by BisectingKMeans.
 
     .. versionadded:: 2.0.0
@@ -487,8 +481,6 @@ class BisectingKMeansModel(JavaModel, JavaMLWritable, JavaMLReadable):
 class BisectingKMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIter, HasSeed,
                       JavaMLWritable, JavaMLReadable):
     """
-    .. note:: Experimental
-
     A bisecting k-means algorithm based on the paper "A comparison of document clustering
     techniques" by Steinbach, Karypis, and Kumar, with modification to fit Spark.
     The algorithm starts from a single cluster that contains all points.
@@ -619,8 +611,6 @@ class BisectingKMeansSummary(ClusteringSummary):
 @inherit_doc
 class LDAModel(JavaModel):
     """
-    .. note:: Experimental
-
     Latent Dirichlet Allocation (LDA) model.
     This abstraction permits for different underlying representations,
     including local and distributed data structures.
@@ -697,8 +687,6 @@ class LDAModel(JavaModel):
 @inherit_doc
 class DistributedLDAModel(LDAModel, JavaMLReadable, JavaMLWritable):
     """
-    .. note:: Experimental
-
     Distributed model fitted by :py:class:`LDA`.
     This type of model is currently only produced by Expectation-Maximization (EM).
 
@@ -761,8 +749,6 @@ class DistributedLDAModel(LDAModel, JavaMLReadable, JavaMLWritable):
 @inherit_doc
 class LocalLDAModel(LDAModel, JavaMLReadable, JavaMLWritable):
     """
-    .. note:: Experimental
-
     Local (non-distributed) model fitted by :py:class:`LDA`.
     This model stores the inferred topics only; it does not store info about the training dataset.
 
@@ -775,8 +761,6 @@ class LocalLDAModel(LDAModel, JavaMLReadable, JavaMLWritable):
 class LDA(JavaEstimator, HasFeaturesCol, HasMaxIter, HasSeed, HasCheckpointInterval,
           JavaMLReadable, JavaMLWritable):
     """
-    .. note:: Experimental
-
     Latent Dirichlet Allocation (LDA), a topic model designed for text documents.
 
     Terminology:
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 40b63d4d31..aada38d1ad 100755
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -654,8 +654,6 @@ class IDFModel(JavaModel, JavaMLReadable, JavaMLWritable):
 @inherit_doc
 class MaxAbsScaler(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWritable):
     """
-    .. note:: Experimental
-
     Rescale each feature individually to range [-1, 1] by dividing through the largest maximum
     absolute value in each feature. It does not shift/center the data, and thus does not destroy
     any sparsity.
@@ -715,8 +713,6 @@ class MaxAbsScaler(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, Jav
 
 class MaxAbsScalerModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
-    .. note:: Experimental
-
     Model fitted by :py:class:`MaxAbsScaler`.
 
     .. versionadded:: 2.0.0
diff --git a/python/pyspark/ml/util.py b/python/pyspark/ml/util.py
index bec4b28952..c65b3d14be 100644
--- a/python/pyspark/ml/util.py
+++ b/python/pyspark/ml/util.py
@@ -62,8 +62,6 @@ class Identifiable(object):
 @inherit_doc
 class MLWriter(object):
     """
-    .. note:: Experimental
-
     Utility class that can save ML instances.
 
     .. versionadded:: 2.0.0
@@ -129,8 +127,6 @@ class JavaMLWriter(MLWriter):
 @inherit_doc
 class MLWritable(object):
     """
-    .. note:: Experimental
-
     Mixin for ML instances that provide :py:class:`MLWriter`.
 
     .. versionadded:: 2.0.0
@@ -159,8 +155,6 @@ class JavaMLWritable(MLWritable):
 @inherit_doc
 class MLReader(object):
     """
-    .. note:: Experimental
-
     Utility class that can load ML instances.
 
     .. versionadded:: 2.0.0
@@ -242,8 +236,6 @@ class JavaMLReader(MLReader):
 @inherit_doc
 class MLReadable(object):
     """
-    .. note:: Experimental
-
     Mixin for instances that provide :py:class:`MLReader`.
 
     .. versionadded:: 2.0.0