not check metrics w/o eval set (#212)

python-package/lightgbm/sklearn.py

@@ -564,7 +564,7 @@ class LGBMClassifier(LGBMModel, LGBMClassifierBase):
         if self.n_classes > 2:
             # Switch to using a multiclass objective in the underlying LGBM instance
             self.objective = "multiclass"
-            if eval_set is not None and eval_metric == "binary_logloss":
+            if eval_metric == "binary_logloss":
                 eval_metric = "multi_logloss"
 
         if eval_set is not None:

src/io/config.cpp

@@ -147,6 +147,7 @@ void OverallConfig::CheckParamConflict() {
       Log::Fatal("Number of classes must be 1 for non-multiclass training");
     }
   }
+  if (boosting_config.is_provide_training_metric || !io_config.valid_data_filenames.empty()) {
     for (std::string metric_type : metric_types) {
       bool metric_type_multiclass = (metric_type == std::string("multi_logloss") || metric_type == std::string("multi_error"));
       if ((objective_type_multiclass && !metric_type_multiclass)
@@ -154,6 +155,7 @@ void OverallConfig::CheckParamConflict() {
         Log::Fatal("Objective and metrics don't match");
       }
     }
+  }
 
   if (network_config.num_machines > 1) {
     is_parallel = true;