Updated documentation for

mllib/src/main/scala/org/apache/spark/ml/feature/VectorSizeHint.scala

@@ -70,17 +70,23 @@ class VectorSizeHint @Since("2.3.0") (@Since("2.3.0") override val uid: String)
   /**
    * Param for how to handle invalid entries. Invalid vectors include nulls and vectors with the
    * wrong size. The options are `skip` (filter out rows with invalid vectors), `error` (throw an
-   * error) and `keep` (do not check the vector size, and keep all rows). `error` by default.
+   * error) and `optimistic` (do not check the vector size, and keep all row\). `error` by default.
+   *
+   * Note: Users should take care when setting this param to `optimistic`. The use of the
+   * `optimistic` option will prevent the transformer from validating the sizes of vectors in
+   * `inputCol`. A mismatch between the metadata of a column and its contents could result in
+   * unexpected behaviour or errors when using that column.
+   *
    * @group param
    */
   @Since("2.3.0")
   override val handleInvalid: Param[String] = new Param[String](
     this,
     "handleInvalid",
     "How to handle invalid vectors in inputCol. Invalid vectors include nulls and vectors with " +
-      "the wrong size. The options are skip (filter out rows with invalid vectors), error " +
-      "(throw an error) and keep (do not check the vector size, and keep all rows). `error` by " +
-      "default.",
+      "the wrong size. The options are `skip` (filter out rows with invalid vectors), `error` " +
+      "(throw an error) and `optimistic` (do not check the vector size, and keep all rows). " +
+      "`error` by default.",
     ParamValidators.inArray(VectorSizeHint.supportedHandleInvalids))
 
   /** @group setParam */
@@ -173,6 +179,7 @@ class VectorSizeHint @Since("2.3.0") (@Since("2.3.0") override val uid: String)
   override def copy(extra: ParamMap): this.type = defaultCopy(extra)
 }
 
+/** :: Experimental :: */
 @Experimental
 @Since("2.3.0")
 object VectorSizeHint extends DefaultParamsReadable[VectorSizeHint] {