Mean error (not squared) in scikit-learn cross_val_score
from sklearn.datasets import load_diabetes
from sklearn.metrics import make_scorer
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import cross_val_score

def mean_error(y, y_pred):
    # assuming y and y_pred are numpy arrays
    return np.mean(y_pred - y)

X, y = load_diabetes(return_X_y=True)
mean_error_scorer = make_scorer(mean_error, greater_is_better=False)

regr = LinearRegression()
cross_val_score(regr, X, y, scoring=mean_error_scorer)