[SPARK-16127][ML][PYPSARK] Audit @Since annotations related to ml.linalg

[SPARK-14615](https://issues.apache.org/jira/browse/SPARK-14615) and #12627 changed `spark.ml` pipelines to use the new `ml.linalg` classes for `Vector`/`Matrix`. Some `Since` annotations for public methods/vals have not been updated accordingly to be `2.0.0`. This PR updates them.

## How was this patch tested?

Existing unit tests.

Author: Nick Pentreath <nickp@za.ibm.com>

Closes #13840 from MLnick/SPARK-16127-ml-linalg-since.

2 files changed, 10 insertions, 6 deletions

diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index d6d713ca53..c035942f73 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -224,7 +224,7 @@ class LogisticRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
     """
 
     @property
-    @since("1.6.0")
+    @since("2.0.0")
     def coefficients(self):
         """
         Model coefficients.
@@ -1051,7 +1051,7 @@ class NaiveBayesModel(JavaModel, JavaMLWritable, JavaMLReadable):
     """
 
     @property
-    @since("1.5.0")
+    @since("2.0.0")
     def pi(self):
         """
         log of class priors.
@@ -1059,7 +1059,7 @@ class NaiveBayesModel(JavaModel, JavaMLWritable, JavaMLReadable):
         return self._call_java("pi")
 
     @property
-    @since("1.5.0")
+    @since("2.0.0")
     def theta(self):
         """
         log of class conditional probabilities.
@@ -1260,7 +1260,7 @@ class MultilayerPerceptronClassificationModel(JavaModel, JavaMLWritable, JavaMLR
         return self._call_java("javaLayers")
 
     @property
-    @since("1.6.0")
+    @since("2.0.0")
     def weights(self):
         """
         vector of initial weights for the model that consists of the weights of layers.
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py
index 29efd6a852..8de9ad8531 100644
--- a/python/pyspark/ml/regression.py
+++ b/python/pyspark/ml/regression.py
@@ -138,7 +138,7 @@ class LinearRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
     """
 
     @property
-    @since("1.6.0")
+    @since("2.0.0")
     def coefficients(self):
         """
         Model coefficients.
@@ -511,6 +511,7 @@ class IsotonicRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
     """
 
     @property
+    @since("2.0.0")
     def boundaries(self):
         """
         Boundaries in increasing order for which predictions are known.
@@ -518,6 +519,7 @@ class IsotonicRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
         return self._call_java("boundaries")
 
     @property
+    @since("2.0.0")
     def predictions(self):
         """
         Predictions associated with the boundaries at the same index, monotone because of isotonic
@@ -1248,7 +1250,7 @@ class AFTSurvivalRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
     """
 
     @property
-    @since("1.6.0")
+    @since("2.0.0")
     def coefficients(self):
         """
         Model coefficients.
@@ -1271,12 +1273,14 @@ class AFTSurvivalRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
         """
         return self._call_java("scale")
 
+    @since("2.0.0")
     def predictQuantiles(self, features):
         """
         Predicted Quantiles
         """
         return self._call_java("predictQuantiles", features)
 
+    @since("2.0.0")
     def predict(self, features):
         """
         Predicted value