1 files changed, 26 insertions, 13 deletions
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 983b6a5301..497f2ad68e 100755
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -352,7 +352,7 @@ class CountVectorizerModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by CountVectorizer.
+    Model fitted by :py:class:`CountVectorizer`.
 
     .. versionadded:: 1.6.0
     """
@@ -609,7 +609,7 @@ class IDF(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWritab
     """
 
     minDocFreq = Param(Params._dummy(), "minDocFreq",
-                       "minimum of documents in which a term should appear for filtering",
+                       "minimum number of documents in which a term should appear for filtering",
                        typeConverter=TypeConverters.toInt)
 
     @keyword_only
@@ -655,7 +655,7 @@ class IDFModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by IDF.
+    Model fitted by :py:class:`IDF`.
 
     .. versionadded:: 1.4.0
     """
@@ -1302,7 +1302,8 @@ class RegexTokenizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
 
     minTokenLength = Param(Params._dummy(), "minTokenLength", "minimum token length (>= 0)",
                            typeConverter=TypeConverters.toInt)
-    gaps = Param(Params._dummy(), "gaps", "whether regex splits on gaps (True) or matches tokens")
+    gaps = Param(Params._dummy(), "gaps", "whether regex splits on gaps (True) or matches tokens " +
+                 "(False)")
     pattern = Param(Params._dummy(), "pattern", "regex pattern (Java dialect) used for tokenizing",
                     typeConverter=TypeConverters.toString)
     toLowercase = Param(Params._dummy(), "toLowercase", "whether to convert all characters to " +
@@ -1549,7 +1550,7 @@ class StandardScalerModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by StandardScaler.
+    Model fitted by :py:class:`StandardScaler`.
 
     .. versionadded:: 1.4.0
     """
@@ -1641,7 +1642,7 @@ class StringIndexerModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by StringIndexer.
+    Model fitted by :py:class:`StringIndexer`.
 
     .. versionadded:: 1.4.0
     """
@@ -1907,7 +1908,7 @@ class VectorIndexer(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, Ja
     """
     .. note:: Experimental
 
-    Class for indexing categorical feature columns in a dataset of [[Vector]].
+    Class for indexing categorical feature columns in a dataset of `Vector`.
 
     This has 2 usage modes:
       - Automatically identify categorical features (default behavior)
@@ -2023,7 +2024,17 @@ class VectorIndexerModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by VectorIndexer.
+    Model fitted by :py:class:`VectorIndexer`.
+
+    Transform categorical features to use 0-based indices instead of their original values.
+      - Categorical features are mapped to indices.
+      - Continuous features (columns) are left unchanged.
+
+    This also appends metadata to the output column, marking features as Numeric (continuous),
+    Nominal (categorical), or Binary (either continuous or categorical).
+    Non-ML metadata is not carried over from the input to the output column.
+
+    This maintains vector sparsity.
 
     .. versionadded:: 1.4.0
     """
@@ -2296,7 +2307,7 @@ class Word2VecModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by Word2Vec.
+    Model fitted by :py:class:`Word2Vec`.
 
     .. versionadded:: 1.4.0
     """
@@ -2327,7 +2338,8 @@ class PCA(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWritab
     """
     .. note:: Experimental
 
-    PCA trains a model to project vectors to a low-dimensional space using PCA.
+    PCA trains a model to project vectors to a lower dimensional space of the
+    top :py:attr:`k` principal components.
 
     >>> from pyspark.ml.linalg import Vectors
     >>> data = [(Vectors.sparse(5, [(1, 1.0), (3, 7.0)]),),
@@ -2401,7 +2413,7 @@ class PCAModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by PCA.
+    Model fitted by :py:class:`PCA`. Transforms vectors to a lower dimensional space.
 
     .. versionadded:: 1.5.0
     """
@@ -2532,7 +2544,8 @@ class RFormulaModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by :py:class:`RFormula`.
+    Model fitted by :py:class:`RFormula`. Fitting is required to determine the
+    factor levels of formula terms.
 
     .. versionadded:: 1.5.0
     """
@@ -2624,7 +2637,7 @@ class ChiSqSelectorModel(JavaModel, JavaMLReadable, JavaMLWritable):
     """
     .. note:: Experimental
 
-    Model fitted by ChiSqSelector.
+    Model fitted by :py:class:`ChiSqSelector`.
 
     .. versionadded:: 2.0.0
     """