Rename binomial loss to bernoulli loss

Author: pierrenodet

core/src/main/scala/org/apache/spark/ml/boosting/GBMLoss.scala

@@ -290,7 +290,7 @@ case object ExponentialLoss
 
 }
 
-case object BinomialLoss extends GBMClassificationLoss with GBMScalarLoss with HasScalarHessian {
+case object BernoulliLoss extends GBMClassificationLoss with GBMScalarLoss with HasScalarHessian {
 
   override def dim: Int = 1
 

core/src/main/scala/org/apache/spark/ml/classification/GBMClassifier.scala

@@ -76,7 +76,7 @@ private[ml] trait GBMClassifierParams extends GBMParams with HasParallelism {
 
   /**
    * Loss function which GBM tries to minimize. (case-insensitive) Supported: "logloss",
-   * "exponential", "binomial". (default = logloss)
+   * "exponential", "bernoulli". (default = logloss)
    *
    * @group param
    */
@@ -100,7 +100,7 @@ private[ml] trait GBMClassifierParams extends GBMParams with HasParallelism {
 private[ml] object GBMClassifierParams {
 
   final val supportedLossTypes: Array[String] =
-    Array("logloss", "exponential", "binomial").map(_.toLowerCase(Locale.ROOT))
+    Array("logloss", "exponential", "bernoulli").map(_.toLowerCase(Locale.ROOT))
 
   final val supportedInitStrategy: Array[String] =
     Array("uniform", "prior").map(_.toLowerCase(Locale.ROOT))
@@ -109,7 +109,7 @@ private[ml] object GBMClassifierParams {
     loss match {
       case "logloss" => LogLoss(numClasses)
       case "exponential" => ExponentialLoss
-      case "binomial" => BinomialLoss
+      case "bernoulli" => BernoulliLoss
       case _ => throw new RuntimeException(s"GBMClassifier was given bad loss type: $loss")
     }
 

core/src/test/scala/org/apache/spark/ml/classification/GBMClassifierSuite.scala

@@ -86,7 +86,7 @@ class GBMClassifierSuite extends AnyFunSuite with BeforeAndAfterAll {
 
   }
 
-  test("gbm exponential and binomial binary classification is better than baselines") {
+  test("gbm exponential and bernoulli binary classification is better than baselines") {
 
     val data =
       spark.read
@@ -110,7 +110,7 @@ class GBMClassifierSuite extends AnyFunSuite with BeforeAndAfterAll {
       .setBaseLearner(dtr)
       .setNumBaseLearners(numBaseLearners)
       .setLearningRate(1.0)
-      .setLoss("binomial")
+      .setLoss("bernoulli")
       .setUpdates("newton")
     val dtc = new DecisionTreeClassifier()
       .setMaxDepth(maxDepth)
@@ -204,15 +204,15 @@ class GBMClassifierSuite extends AnyFunSuite with BeforeAndAfterAll {
     val gbmrWithVal = new GBMClassifier()
       .setBaseLearner(dtr)
       .setNumBaseLearners(10)
-      .setLoss("binomial")
+      .setLoss("bernoulli")
       .setUpdates("gradient")
       .setValidationIndicatorCol("validation")
       .setNumRounds(1)
 
     val gbmrNoVal = new GBMClassifier()
       .setBaseLearner(dtr)
       .setNumBaseLearners(10)
-      .setLoss("binomial")
+      .setLoss("bernoulli")
       .setUpdates("gradient")
 
     val mce = new MulticlassClassificationEvaluator().setMetricName("logLoss")