TST check all importance_types for XGBoost

tests/test_xgboost.py

@@ -31,8 +31,10 @@
 )
 
 
-def test_explain_xgboost(newsgroups_train):
-    _check_rf_classifier(newsgroups_train, XGBClassifier(n_estimators=10))
+@pytest.mark.parametrize(['importance_type'], [['gain'], ['weight'], ['cover']])
+def test_explain_xgboost(newsgroups_train, importance_type):
+    _check_rf_classifier(newsgroups_train, XGBClassifier(n_estimators=10),
+                         importance_type=importance_type)
 
 
 def test_explain_booster(newsgroups_train):
@@ -452,14 +454,14 @@ def test_check_booster_args():
     regressor = XGBRegressor().fit(x, y)
     classifier = XGBClassifier().fit(x, y)
     booster, is_regression = _check_booster_args(regressor)
-    assert is_regression == True
+    assert is_regression is True
     assert isinstance(booster, xgboost.Booster)
     _, is_regression = _check_booster_args(regressor, is_regression=True)
-    assert is_regression == True
+    assert is_regression is True
     _, is_regression = _check_booster_args(classifier)
-    assert is_regression == False
+    assert is_regression is False
     _, is_regression = _check_booster_args(classifier, is_regression=False)
-    assert is_regression == False
+    assert is_regression is False
     with pytest.raises(ValueError):
         _check_booster_args(classifier, is_regression=True)
     with pytest.raises(ValueError):
@@ -469,4 +471,4 @@ def test_check_booster_args():
     assert _booster is booster
     assert is_regression is None
     _, is_regression = _check_booster_args(booster, is_regression=True)
-    assert is_regression == True
+    assert is_regression is True