diff --git a/python-package/xgboost/training.py b/python-package/xgboost/training.py
index ca95f46cb..759f30221 100644
--- a/python-package/xgboost/training.py
+++ b/python-package/xgboost/training.py
@@ -38,7 +38,7 @@ def _train_internal(params, dtrain,
 
     _params = dict(params) if isinstance(params, list) else params
 
-    if 'num_parallel_tree' in _params and params[
+    if 'num_parallel_tree' in _params and _params[
             'num_parallel_tree'] is not None:
         num_parallel_tree = _params['num_parallel_tree']
         nboost //= num_parallel_tree
diff --git a/tests/python/test_with_sklearn.py b/tests/python/test_with_sklearn.py
index d29de0464..0a58f3af5 100644
--- a/tests/python/test_with_sklearn.py
+++ b/tests/python/test_with_sklearn.py
@@ -34,7 +34,8 @@ def test_binary_classification():
     kf = KFold(n_splits=2, shuffle=True, random_state=rng)
     for cls in (xgb.XGBClassifier, xgb.XGBRFClassifier):
         for train_index, test_index in kf.split(X, y):
-            xgb_model = cls(random_state=42).fit(X[train_index], y[train_index])
+            clf = cls(random_state=42)
+            xgb_model = clf.fit(X[train_index], y[train_index], eval_metric=['auc', 'logloss'])
             preds = xgb_model.predict(X[test_index])
             labels = y[test_index]
             err = sum(1 for i in range(len(preds))