Add option to disable default metric (#3606)

demo/guide-python/custom_objective.py

@@ -33,9 +33,9 @@ def logregobj(preds, dtrain):
 # Take this in mind when you use the customization, and maybe you need write customized evaluation function
 def evalerror(preds, dtrain):
     labels = dtrain.get_label()
-    # return a pair metric_name, result. The metric name must not contain a colon (:)
+    # return a pair metric_name, result. The metric name must not contain a colon (:) or a space
     # since preds are margin(before logistic transformation, cutoff at 0)
-    return 'error', float(sum(labels != (preds > 0.0))) / len(labels)
+    return 'my-error', float(sum(labels != (preds > 0.0))) / len(labels)
 
 # training with customized objective, we can also do step by step training
 # simply look at xgboost.py's implementation of train

doc/parameter.rst

@@ -31,6 +31,10 @@ General Parameters
 
   - Number of parallel threads used to run XGBoost
 
+* ``disable_default_eval_metric`` [default=0]
+
+  - Flag to disable default metric. Set to >0 to disable.
+
 * ``num_pbuffer`` [set automatically by XGBoost, no need to be set by user]
 
   - Size of prediction buffer, normally set to number of training instances. The buffers are used to save the prediction results of last boosting step.

src/learner.cc

@@ -92,6 +92,8 @@ struct LearnerTrainParam : public dmlc::Parameter<LearnerTrainParam> {
   int nthread;
   // flag to print out detailed breakdown of runtime
   int debug_verbose;
+  // flag to disable default metric
+  int disable_default_eval_metric;
   // declare parameters
   DMLC_DECLARE_PARAMETER(LearnerTrainParam) {
     DMLC_DECLARE_FIELD(seed).set_default(0).describe(
@@ -128,6 +130,9 @@ struct LearnerTrainParam : public dmlc::Parameter<LearnerTrainParam> {
         .set_lower_bound(0)
         .set_default(0)
         .describe("flag to print out detailed breakdown of runtime");
+    DMLC_DECLARE_FIELD(disable_default_eval_metric)
+        .set_default(0)
+        .describe("flag to disable default metric. Set to >0 to disable");
   }
 };
 
@@ -403,7 +408,7 @@ class LearnerImpl : public Learner {
     monitor_.Start("EvalOneIter");
     std::ostringstream os;
     os << '[' << iter << ']' << std::setiosflags(std::ios::fixed);
-    if (metrics_.size() == 0) {
+    if (metrics_.size() == 0 && tparam_.disable_default_eval_metric <= 0) {
       metrics_.emplace_back(Metric::Create(obj_->DefaultEvalMetric()));
     }
     for (size_t i = 0; i < data_sets.size(); ++i) {