sklearn中的线性回归

#一元线型回归模型

print("一元线型回归模型")

import sklearn.linear_model as lm

import numpy as np

x=[1,3,5,7]

x=(x).reshape(-1,1)

print(x)

y = ([2, 4, 6, 8])

model=()

(x,y)

print("Intercept:",model.intercept_)

print("Coefficients:",model.coef_)

print("Prediction for 60:",(([60]).reshape((-1, 1))))

#二元线型回归模型（多元线型回归与此类似）

print("二元线型回归模型")

x1=[1,2,3,4]

x2=[2,4,6,8]

#矩形转置

x=([x1,x2]).T

print(x)

x=([x1,x2]).reshape(-1,2)

y = ([2, 4, 6, 8])

model=()

(x,y)

print("Intercept:",model.intercept_)

print("Coefficients:",model.coef_)

print("Prediction for [60,60]:",(([60,60]).reshape((-1, 2))))