如何在Python中用ARIMA模型评价预测结果

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from statsmodels.tsa.arima_model import ARIMA

data = pd.read_csv('data.csv', parse_dates=['date'], index_col='date')

train_data = data[:'2021-01-01']
test_data = data['2021-01-02':]

model = ARIMA(train_data, order=(p, d, q))
model_fit = model.fit(disp=0)

predictions = model_fit.predict(start='2021-01-02', end='2021-01-31')

from sklearn.metrics import mean_squared_error, mean_absolute_error

mse = mean_squared_error(test_data, predictions)
mae = mean_absolute_error(test_data, predictions)
mape = np.mean(np.abs((test_data - predictions) / test_data)) * 100

print("均方根误差（RMSE）：", np.sqrt(mse))
print("平均绝对误差（MAE）：", mae)
print("平均绝对百分比误差（MAPE）：", mape)