[英]Get p,q,d and P, D, Q, m values from auto-arima summary
您可以使用以下技术来解决您的问题,
#In this case I have used model of ARIMA,
#You can convert model.summary in string format and find its parameters
#using regular expression.
import re
summary_string = str(model.summary())
param = re.findall('ARIMA\(([0-9]+), ([0-9]+), ([0-9]+)',summary_string)
p,d,q = int(param[0][0]) , int(param[0][1]) , int(param[0][2])
print(p,d,q)
最终输出: 单击此处查看我的 model.summary() 输出。
通过这种方式,您可以在循环的帮助下存储所有模型的参数值。
要从 AutoARIMA 模型摘要中获取 order 和 season_order 值,我们可以使用 get_params()。
https://scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html
单击下面的链接以获得更好的图片。
model = auto_arima(df_weekly1['Value'], start_p = 1, start_q = 1,
max_p = 3, max_q = 3, m = 12,
start_P = 0, seasonal = True,
d = None, D = 1, trace = True)
model.summary()
我们可以使用 get_params() 获取模型摘要值,get_params 函数的输出将是 dict 数据类型。
get_parametes = model.get_params()
print(type(get_parametes))
get_parametes
order_aa = get_parametes.get('order')
seasonal_order_aa = get_parametes.get('seasonal_order')
print('order:', order_aa)
print('seasonal_order:', seasonal_order_aa)
print('order DTYPE:', type(order_aa))
print('seasonal_order DTYPE:', type(seasonal_order_aa))
model_ss = SARIMAX(train['Col_Name'],
order = (order_aa[0], order_aa[1], order_aa[2]),
seasonal_order =(seasonal_order_aa[0],
seasonal_order_aa[1], seasonal_order_aa[2], seasonal_order_aa[3]))
result_ss = model_ss.fit()
result_ss.summary()
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