OneVsRest Issue with MLeap 0.14.0 , 0.15.0

Scala Version - 2.11
Spark Version - 2.4.3

Hi,
I have a pipeline configured with the following sparkML transformers & algorithms. I have been trying to solve a multiclassification problem using LinearSVC & OneVSRest.

```
val stringIndexer = new org.apache.spark.ml.feature.StringIndexer().setInputCol("label").setOutputCol("label_indexed").setHandleInvalid("skip")
val tokenizer = new org.apache.spark.ml.feature.Tokenizer().setInputCol("text").setOutputCol("words")
val hashingTF = new org.apache.spark.ml.feature.HashingTF().setNumFeatures(1000).setInputCol(tokenizer.getOutputCol).setOutputCol("features")
val lsvc = new org.apache.spark.ml.classification.LinearSVC().setLabelCol("label_indexed").setFeaturesCol("features")
val mleapOVR = new org.apache.spark.ml.mleap.classification.OneVsRest().setClassifier(lsvc).setLabelCol("label_indexed").setFeaturesCol("features")
val sparkmlOVR = new org.apache.spark.ml.classification.OneVsRest().setClassifier(lsvc).setLabelCol("label_indexed").setFeaturesCol("features")
val indexToString = new org.apache.spark.ml.feature.IndexToString().setInputCol("prediction").setOutputCol("predictedCategory").setLabels(stringIndexer.fit(df).labels)

val model = new Pipeline().setStages(Array(stringIndexer, tokenizer, hashingTF, mleapOVR, indexToString)).fit(df)
val predictionDf = model.transform(df)
predictionDf.show()

+---+--------------------+------+-------------+--------------------+--------------------+------------------------------------------+----------+------------------+-----------------+
| id| text| label|label_indexed| words| features|mbc$lpc539bff7-6d99-4077-bfb1-ce2fea8b632b|prediction| probability|predictedCategory|
+---+--------------------+------+-------------+--------------------+--------------------+------------------------------------------+----------+------------------+-----------------+
| 0|a table-tennis an...|sports| 0.0|[a, table-tennis,...|(1000,[170,273,33...| [0, 1.45738526075...| 0| 1.45738526075102| sports|
| 1| pool c d|sports| 0.0| [pool, c, d]|(1000,[94,722,860...| [0, 2.06780485158...| 0|2.0678048515897625| sports|
| 2| h cricket f hockey|sports| 0.0|[h, cricket, f, h...|(1000,[2,220,248,...| [0, 2.06780485158...| 0|2.0678048515897625| sports|
| 3| alien i u predator|movies| 1.0|[alien, i, u, pre...|(1000,[329,352,52...| [1, 1.44052588695...| 1|1.4405258869594206| movies|
| 4| terminator is back|movies| 1.0|[terminator, is, ...|(1000,[182,281,43...| [1, 2.34671134516...| 1|2.3467113451695374| movies|
| 5| v r gladiator|movies| 1.0| [v, r, gladiator]|(1000,[248,477,57...| [1, 1.53089091952...| 1|1.5308909195231362| movies|
| 6|hi badminton hey ...|sports| 0.0|[hi, badminton, h...|(1000,[170,559,92...| [0, 1.63159124054...| 0|1.6315912405409212| sports|
| 7| rambo is lit|movies| 1.0| [rambo, is, lit]|(1000,[281,661,81...| [1, 2.34671134516...| 1|2.3467113451695374| movies|
| 8| you chess me hockey|sports| 0.0|[you, chess, me, ...|(1000,[2,425,471,...| [0, 1.34536377753...| 0|1.3453637775364258| sports|
| 9| we play checkers|sports| 0.0|[we, play, checkers]|(1000,[173,902,99...| [0, 2.17738374250...| 0|2.1773837425059606| sports|
| 10| be like rocky|movies| 1.0| [be, like, rocky]|(1000,[330,656,74...| [1, 2.27254585192...| 1| 2.272545851928956| movies|
| 11| i m joker|movies| 1.0| [i, m, joker]|(1000,[36,329,638...| [1, 2.16296696101...| 1|2.1629669610127578| movies|
+---+--------------------+------+-------------+--------------------+--------------------+------------------------------------------+----------+------------------+-----------------+
```

I need to serialize the pipelineModel to deploy it on sagemaker. So, if I try to use **sparkMLOVR** instance in the pipeline it doesn't work. I switched to **mLeapOVR** instance and used the following code to _serialize the model to zip_ :

```
val simpleSparkSerializerObj = new SimpleSparkSerializer
simpleSparkSerializerObj.serializeToBundleWithFormat(model, "jar:file:/C:/tmp/ovr.zip", predictionDf, SerializationFormat.Json)
```
**Issue with 0.14.0 while serializing** : The zip that it creates doesn't have the model.json artifacts for OneVsRest and that directory is empty. So, if I try to deserialize it back using the following code, it throws an Exception :

```
val bundle = (for (bundleFile <- managed(BundleFile("jar:file:/C:/tmp/ovr.zip"))) yield { bundleFile.loadSparkBundle().get }).opt.get.root

Exception in thread "main" java.util.NoSuchElementException: None.get
at scala.None$.get(Option.scala:347)
at scala.None$.get(Option.scala:345)
```
If I use **MLeap 0.15.0 to serialize & deserialize** the zip back to a transformer, it doesn't throw the above exception. But when I try to transform it on the df, it throws the following exception :

```
bundle.transform(df).show()
Exception in thread "main" java.util.NoSuchElementException: Failed to find a default value for classifier
at org.apache.spark.ml.param.Params$$anonfun$getOrDefault$2.apply(params.scala:780)
at org.apache.spark.ml.param.Params$$anonfun$getOrDefault$2.apply(params.scala:780)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.ml.param.Params$class.getOrDefault(params.scala:779)
at org.apache.spark.ml.PipelineStage.getOrDefault(Pipeline.scala:42)
at org.apache.spark.ml.param.Params$class.$(params.scala:786)
at org.apache.spark.ml.PipelineStage.$(Pipeline.scala:42)
at org.apache.spark.ml.mleap.classification.OneVsRestParams$class.getClassifier(OneVsRest.scala:70)
at org.apache.spark.ml.mleap.classification.OneVsRestModel.getClassifier(OneVsRest.scala:137)
at org.apache.spark.ml.mleap.classification.OneVsRestModel.transformSchema(OneVsRest.scala:154)
at org.apache.spark.ml.PipelineModel$$anonfun$transformSchema$5.apply(Pipeline.scala:311)
at org.apache.spark.ml.PipelineModel$$anonfun$transformSchema$5.apply(Pipeline.scala:311)
at scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)
at scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)
at scala.collection.mutable.ArrayOps$ofRef.foldLeft(ArrayOps.scala:186)
at org.apache.spark.ml.PipelineModel.transformSchema(Pipeline.scala:311)
at org.apache.spark.ml.PipelineStage.transformSchema(Pipeline.scala:74)
at org.apache.spark.ml.PipelineModel.transform(Pipeline.scala:305)
```

Is there an issue with OneVsRest provided by MLeap Spark Extension 0.15.0 for 2.4.3?

A quick response and resolution would be much appreciated. Thank you