python线性回归按日期预测 [英] python linear regression predict by date
本文介绍了python线性回归按日期预测的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我想通过简单的线性回归来预测将来某个日期的值,但是由于日期格式,我无法.
I want to predict a value at a date in the future with simple linear regression, but I can't due to the date format.
这是我拥有的数据框:
data_df =
date value
2016-01-15 1555
2016-01-16 1678
2016-01-17 1789
...
y = np.asarray(data_df['value'])
X = data_df[['date']]
X_train, X_test, y_train, y_test = train_test_split
(X,y,train_size=.7,random_state=42)
model = LinearRegression() #create linear regression object
model.fit(X_train, y_train) #train model on train data
model.score(X_train, y_train) #check score
print (‘Coefficient: \n’, model.coef_)
print (‘Intercept: \n’, model.intercept_)
coefs = zip(model.coef_, X.columns)
model.__dict__
print "sl = %.1f + " % model.intercept_ + \
" + ".join("%.1f %s" % coef for coef in coefs) #linear model
我尝试将日期转换失败
data_df['conv_date'] = data_df.date.apply(lambda x: x.toordinal())
data_df['conv_date'] = pd.to_datetime(data_df.date, format="%Y-%M-%D")
推荐答案
线性回归不适用于日期数据.因此我们需要将其转换为数值.以下代码会将日期转换为数值:
Linear regression doesn't work on date data. Therefore we need to convert it into numerical value.The following code will convert the date into numerical value:
import datetime as dt
data_df['Date'] = pd.to_datetime(data_df['Date'])
data_df['Date']=data_df['Date'].map(dt.datetime.toordinal)
这篇关于python线性回归按日期预测的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!
查看全文