如何使 intertools arima grid-search 运行更快

Question

我有一个带有 intertools 的 ARIMA 网格搜索函数，我相信它可以为我提供 400 个数据集的 time-series 数据的最佳 ARIMA 模型，但它已经运行ning 72 小时实际出结果但太慢了。我怎样才能在几分钟内非常非常快地达到运行？

我试过 d=0, p=q=range(0,3) 代替 p = d = q = range(0, 3)，这给了我错误。

# Generate the `ts` data 
import numpy as np
import pandas as pd
from datetime import datetime

date_rng = pd.date_range('1985-01', periods=400, freq='M')
ts = pd.DataFrame(date_rng, columns=['date'])
ts['data'] = np.random.randint(0,100,size=(len(date_rng)))
ts.head(5)

.

import warnings
import itertools
warnings.filterwarnings("ignore") # specify to ignore warning messages

# Define the p, d and q parameters to take any value between 0 and 2
p = d = q = range(0, 3)

# Generate all different combinations of p, q and q triplets
pdq = list(itertools.product(p, d, q))

# Generate all different combinations of seasonal p, q and q triplets
seasonal_pdq = [(x[0], x[1], x[2], 12) for x in list(itertools.product(p, d, q))]

print('Examples of parameter combinations for Seasonal ARIMA...')
print('SARIMAX: {} x {}'.format(pdq[1], seasonal_pdq[1]))
print('SARIMAX: {} x {}'.format(pdq[1], seasonal_pdq[2]))
print('SARIMAX: {} x {}'.format(pdq[2], seasonal_pdq[3]))
print('SARIMAX: {} x {}'.format(pdq[2], seasonal_pdq[4]))

.

warnings.filterwarnings("ignore") # specify to ignore warning messages

for param in pdq:
    for param_seasonal in seasonal_pdq:
        try:
            mod = sm.tsa.statespace.SARIMAX(ts,
                                            order=param,
                                            seasonal_order=param_seasonal,
                                            enforce_stationarity=False,
                                            enforce_invertibility=False)

            results = mod.fit()

            print('ARIMA{}x{}12 - AIC:{}'.format(param, param_seasonal, results.aic))
        except:
            continue

我想在几分钟内非常非常快地编写 python 代码

Answer 1

又是我。所以，我试图找到另一种更快的方法，也许解决方案可以使用多处理。我今天尝试了，但我发现了一些小问题，我 post it 有人可以帮助我们。

顺便说一句。同时搜索，我发现了另一种更快的方法，所以如果你有兴趣可以我们这个代码

from pmdarima.arima import auto_arima
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline

series = pd.read_csv('dataset.csv', header=None, index_col=0, parse_dates=True, squeeze=True)
train, test = series[1:900], series[900:]


Arima_model=auto_arima(train, start_p=1, start_q=1, max_p=8, max_q=8, start_P=0, start_Q=0, max_P=8, max_Q=8, m=12, seasonal=True, trace=True, d=1, D=1, error_action='warn', suppress_warnings=True, random_state = 20, n_fits=30)

如何使 intertools arima grid-search 运行更快

How to make intertools arima grid-search run faster

itertools

python-3.x

grid-search

如何使 intertools arima grid-search 运行 更快

How to make intertools arima grid-search run faster

itertools

python-3.x

grid-search

如何使 intertools arima grid-search 运行更快