[SPARK-15096][ML] LogisticRegression MultiClassSummarizer numClasses can fail if no valid labels are found

## What changes were proposed in this pull request?

(Please fill in changes proposed in this fix)
Throw better exception when numClasses is empty and empty.max is thrown.

## How was this patch tested?

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Add a new unit test, which calls histogram with empty numClasses.

Author: [email protected] <[email protected]>

Closes #12969 from wangmiao1981/logisticR.

Author: wangmiao1981

mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala

@@ -745,7 +745,7 @@ private[classification] class MultiClassSummarizer extends Serializable {
   def countInvalid: Long = totalInvalidCnt
 
   /** @return The number of distinct labels in the input dataset. */
-  def numClasses: Int = distinctMap.keySet.max + 1
+  def numClasses: Int = if (distinctMap.isEmpty) 0 else distinctMap.keySet.max + 1
 
   /** @return The weightSum of each label in the input dataset. */
   def histogram: Array[Double] = {

mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala

@@ -256,6 +256,10 @@ class LogisticRegressionSuite
     assert(summarizer4.countInvalid === 2)
     assert(summarizer4.numClasses === 4)
 
+    val summarizer5 = new MultiClassSummarizer
+    assert(summarizer5.histogram.isEmpty)
+    assert(summarizer5.numClasses === 0)
+
     // small map merges large one
     val summarizerA = summarizer1.merge(summarizer2)
     assert(summarizerA.hashCode() === summarizer2.hashCode())