Change DefaultEvalMetric of classification from error to logloss

dmlc · Sep 29, 2020 · e40a9eb · e40a9eb
1 parent 444131a
commit e40a9eb
Show file tree

Hide file tree

Showing 6 changed files with 7 additions and 7 deletions.
diff --git a/doc/parameter.rst b/doc/parameter.rst
@@ -376,7 +376,7 @@ Specify the learning task and the corresponding learning objective. The objectiv
 
 * ``eval_metric`` [default according to objective]
 
-  - Evaluation metrics for validation data, a default metric will be assigned according to objective (rmse for regression, and error for classification, mean average precision for ranking)
+  - Evaluation metrics for validation data, a default metric will be assigned according to objective (rmse for regression, and logloss for classification, mean average precision for ranking)
   - User can add multiple evaluation metrics. Python users: remember to pass the metrics in as list of parameters pairs instead of map, so that latter ``eval_metric`` won't override previous one
   - The choices are listed below:
 

diff --git a/...ages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala b/...ages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala
@@ -154,10 +154,10 @@ class XGBoostClassifier (
     require(isDefined(objective), "Users must set \'objective\' via xgboostParams.")
     if ($(objective).startsWith("multi")) {
       // multi
-      "merror"
+      "mlogloss"
     } else {
       // binary
-      "error"
+      "logloss"
     }
   }
 

diff --git a/plugin/updater_oneapi/regression_loss_oneapi.h b/plugin/updater_oneapi/regression_loss_oneapi.h
@@ -103,7 +103,7 @@ struct LogisticRegressionOneAPI {
 
 // logistic loss for binary classification task
 struct LogisticClassificationOneAPI : public LogisticRegressionOneAPI {
-  static const char* DefaultEvalMetric() { return "error"; }
+  static const char* DefaultEvalMetric() { return "logloss"; }
   static const char* Name() { return "binary:logistic_oneapi"; }
 };
 

diff --git a/src/objective/multiclass_obj.cu b/src/objective/multiclass_obj.cu
@@ -125,7 +125,7 @@ class SoftmaxMultiClassObj : public ObjFunction {
     this->Transform(io_preds, true);
   }
   const char* DefaultEvalMetric() const override {
-    return "merror";
+    return "mlogloss";
   }
 
   inline void Transform(HostDeviceVector<bst_float> *io_preds, bool prob) {

diff --git a/src/objective/regression_loss.h b/src/objective/regression_loss.h
@@ -131,7 +131,7 @@ struct PseudoHuberError {
 
 // logistic loss for binary classification task
 struct LogisticClassification : public LogisticRegression {
-  static const char* DefaultEvalMetric() { return "error"; }
+  static const char* DefaultEvalMetric() { return "logloss"; }
   static const char* Name() { return "binary:logistic"; }
 };
 

diff --git a/tests/cpp/plugin/test_example_objective.cc b/tests/cpp/plugin/test_example_objective.cc
@@ -8,7 +8,7 @@ namespace xgboost {
 TEST(Plugin, ExampleObjective) {
   xgboost::GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
   auto * obj = xgboost::ObjFunction::Create("mylogistic", &tparam);
-  ASSERT_EQ(obj->DefaultEvalMetric(), std::string{"error"});
+  ASSERT_EQ(obj->DefaultEvalMetric(), std::string{"logloss"});
   delete obj;
 }