TST: Added test for parameter tuning using GridSearchCV

tests/python/test_with_sklearn.py

@@ -42,5 +42,16 @@ def test_boston_housing_regression():
 	    labels = y[test_index]
 	assert mean_squared_error(preds, labels) < 9
 
+def test_parameter_tuning():
+	boston = load_boston()
+	y = boston['target']
+	X = boston['data']
+	xgb_model = xgb.XGBRegressor()
+	clf = GridSearchCV(xgb_model,
+	                   {'max_depth': [2,4,6],
+	                    'n_estimators': [50,100,200]}, verbose=1)
+	clf.fit(X,y)
+	assert clf.best_score_ < 0.7
+	assert clf.best_params_ == {'n_estimators': 100, 'max_depth': 4}