import numpy as np
import pandas as pd
from sklearn.metrics import mean_absolute_error
from sklearn.metrics import mean_squared_error

def evaluation(y_true, y_pred):
    y_true, y_pred = np.array(y_true), np.array(y_pred)
    mae = mean_absolute_error(y_true, y_pred)
    mse = mean_squared_error(y_true, y_pred)
    score = pd.DataFrame([mae, mse], index=['mae', 'mse'], columns=['score']).T
    return score