revert stringindexer

Author: hhbyyh

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

@@ -52,10 +52,6 @@ private[feature] trait StringIndexerBase extends Params with HasInputCol with Ha
     val outputFields = inputFields :+ attr.toStructField()
     StructType(outputFields)
   }
-
-  /** @group setParam */
-  def setHandleInvalid(value: String): this.type = set(handleInvalid, value)
-  setDefault(handleInvalid, "error")
 }
 
 /**
@@ -73,6 +69,10 @@ class StringIndexer(override val uid: String) extends Estimator[StringIndexerMod
 
   def this() = this(Identifiable.randomUID("strIdx"))
 
+  /** @group setParam */
+  def setHandleInvalid(value: String): this.type = set(handleInvalid, value)
+  setDefault(handleInvalid, "error")
+
   /** @group setParam */
   def setInputCol(value: String): this.type = set(inputCol, value)
 
@@ -133,6 +133,10 @@ class StringIndexerModel (
     map
   }
 
+  /** @group setParam */
+  def setHandleInvalid(value: String): this.type = set(handleInvalid, value)
+  setDefault(handleInvalid, "error")
+
   /** @group setParam */
   def setInputCol(value: String): this.type = set(inputCol, value)
 

mllib/src/main/scala/org/apache/spark/ml/feature/package-info.java

@@ -23,7 +23,7 @@
  * features into more suitable forms for model fitting.
  * Most feature transformers are implemented as {@link org.apache.spark.ml.Transformer}s, which
  * transforms one {@link org.apache.spark.sql.DataFrame} into another, e.g.,
- * {@link org.apache.spark.mllib.feature.HashingTF}.
+ * {@link org.apache.spark.ml.feature.HashingTF}.
  * Some feature transformers are implemented as {@link org.apache.spark.ml.Estimator}}s, because the
  * transformation requires some aggregated information of the dataset, e.g., document
  * frequencies in {@link org.apache.spark.ml.feature.IDF}.