diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
index cdbd06200c7bd..4b4fc74097862 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
@@ -27,7 +27,7 @@ import org.apache.spark.ml.Transformer
 import org.apache.spark.ml.util.{Identifiable, MetadataUtils}
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.functions._
-import org.apache.spark.sql.types.{NumericType, StringType, StructType}
+import org.apache.spark.sql.types.{DoubleType, NumericType, StringType, StructType}
 import org.apache.spark.util.collection.OpenHashMap
 
 /**
@@ -159,8 +159,7 @@ class StringIndexerModel private[ml] (
    * should only be used on new columns such as predicted labels.
    */
   def invert(inputCol: String, outputCol: String): StringIndexerInverse = {
-    val labelsCol: String = $(this.outputCol)
-    new StringIndexerInverseTransformer(labelsCol)
+    new StringIndexerInverse(Some(labels))
       .setInputCol(inputCol)
       .setOutputCol(outputCol)
   }
@@ -175,10 +174,11 @@ class StringIndexerModel private[ml] (
 @Experimental
 class StringIndexerInverse private[ml] (
   override val uid: String,
-  val labelsCol: String) extends Transformer
+  val labels: Option[Array[String]]) extends Transformer
     with HasInputCol with HasOutputCol {
 
-  def this(labelsCol: String) = this(Identifiable.randomUID("strIdxInv"), labelsCol)
+  def this(labels: Option[Array[String]] = None) =
+    this(Identifiable.randomUID("strIdxInv"), labels)
 
   /** @group setParam */
   def setInputCol(value: String): this.type = set(inputCol, value)
@@ -204,9 +204,10 @@ class StringIndexerInverse private[ml] (
 
   override def transform(dataset: DataFrame): DataFrame = {
     val inputColSchema = dataset.schema($(inputCol))
-    val attr = Attribute.fromStructField(inputColSchema)
-      .asInstanceOf[NominalAttribute]
-    val values = attr.values.get
+    val values = labels.getOrElse{
+      Attribute.fromStructField(inputColSchema)
+        .asInstanceOf[NominalAttribute].values.get
+    }
     val indexer = udf { index: Double =>
       val idx = index.toInt
       if (0 <= idx && idx < values.size) {
@@ -220,8 +221,8 @@ class StringIndexerInverse private[ml] (
       indexer(dataset($(inputCol)).cast(DoubleType)).as(outputColName))
   }
 
-  override def copy(extra: ParamMap): StringIndexerInverseTransformer = {
-    val copied = new StringIndexerInverseTransformer(uid)
+  override def copy(extra: ParamMap): StringIndexerInverse = {
+    val copied = new StringIndexerInverse(uid, labels)
     copyValues(copied, extra)
   }
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
index d13f4999b5487..d0295a0fe2fc1 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
@@ -53,6 +53,13 @@ class StringIndexerSuite extends SparkFunSuite with MLlibTestSparkContext {
       .select("id", "label2")
     assert(df.collect().map(r => (r.getInt(0), r.getString(1))).toSet ===
       reversed.collect().map(r => (r.getInt(0), r.getString(1))).toSet)
+    // Check invert using only metadata
+    val inverse2 = new StringIndexerInverse()
+      .setInputCol("labelIndex")
+      .setOutputCol("label2")
+    val reversed2 = inverse2.transform(transformed).select("id", "label2")
+    assert(df.collect().map(r => (r.getInt(0), r.getString(1))).toSet ===
+      reversed2.collect().map(r => (r.getInt(0), r.getString(1))).toSet)
   }
 
   test("StringIndexer with a numeric input column") {