code: def test_multiclass() -> None:
      X, y = tm.datasets.make_classification(
          128, n_features=12, n_informative=10, n_classes=4
      )
      clf = xgb.XGBClassifier(
          multi_strategy="multi_output_tree",
          callbacks=[ResetStrategy()],
          n_estimators=10,
      )
      clf.fit(X, y, eval_set=[(X, y)])
      assert clf.objective == "multi:softprob"
      assert tm.non_increasing(
          clf.evals_result()["validation_0"]["mlogloss"]
      )
  
      proba = clf.predict_proba(X)
      assert proba.shape == (y.shape[0], 4)
  
file_path: xgboost/tests/python/test_multi_target.py
imports: from typing import Any, Dict
  from hypothesis import given, note, settings, strategies
  import xgboost
  from xgboost import testing
  from xgboost.testing.params import exact_parameter_strategy, hist_cache_strategy, hist_multi_parameter_strategy, hist_parameter_strategy
  from xgboost.testing.updater import ResetStrategy, train_result
label_desc: Use image node_id 1 for calling a global function with example usage: test_multiclass() without return types