多元线性回归

from numpy import genfromtxt #把导入的数据变成Numpy array
import numpy as np
from sklearn import datasets, linear_model   #sklearn是机器学习中的一个库

dataPath = r"D:\MaiziEdu\DeepLearningBasics_MachineLearning\Datasets\Delivery.csv"      #读取数据文件路径
deliveryData = genfromtxt(dataPath, delimiter=‘,‘)   #把数据搞成矩阵形式
print "data"
print deliveryData

X = deliveryData[:, :-1]   #自变量x取第0列到倒数第二列
Y = deliveryData[:, -1]   #因变量即输出y所有行的最后一列

print "X:"
print X
print "Y: "
print Y

regr = linear_model.LinearRegression() #创建模型

regr.fit(X, Y)   #对x和y进行建模

print "coefficients"
print regr.coef_             #打印b1,b2.....
print "intercept: "
print regr.intercept_        #截距即b0

xPred = [102, 6]
yPred = regr.predict(xPred)
print "predicted y: "
print yPred