import xlrd
from numpy.linalg import inv
import numpy as np

data = xlrd.open_workbook(u‘C:\\Users\\xd/Desktop\\作业\\新建文件夹\\线性代数\\SpeedVideoDataforModeling.xlsx‘)
table = data.sheet_by_index(0)
x1 = np.array(table.col_values(17)[1:])
x2 = np.array(table.col_values(18)[1:])
x3 = np.array(table.col_values(19)[1:])
y1 = np.array(table.col_values(20)[1:])
y2 = np.array(table.col_values(21)[1:])
x0 = np.array([1 for i in x1])
X = np.vstack((x0,x1,x2,x3)).T
############最小二乘法多元线性回归#######################
coef1 = np.dot(np.dot(inv(np.dot(X.T,X)),X.T),y1.T)
coef2 = np.dot(np.dot(inv(np.dot(X.T,X)),X.T),y2.T)
from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(X, y1)
print model.coef_
model.fit(X, y2)
print model.coef_
##############小的实例========================
x = [[1,1,1], [1,1,2], [1,2,1]]
y = [[6], [9], [8]]

model = LinearRegression()
model.fit(x, y)