1. 例子

一家快递公司送货：X1： 运输里程 X2： 运输次数   Y：总运输时间     

Driving  Assignment	X1=Miles  Traveled	X2=Number of Deliveries	Y= Travel Time (Hours)
1	100	4	9.3
2	50	3	4.8
3	100	4	8.9
4	100	2	6.5
5	50	2	4.2
6	80	2	6.2
7	75	3	7.4
8	65	4	6.0
9	90	3	7.6
10	90	2	6.1

目的，求出b0, b1,.... bp：

y_hat=b0＋b１x1+b2x2+ ... +bpxp 

2. Python代码：

from numpy import genfromtxt

import numpy as np

from sklearn import datasets, linear_model


dataPath = r"D:\MaiziEdu\DeepLearningBasics_MachineLearning\Datasets\Delivery.csv"

deliveryData = genfromtxt(dataPath, delimiter=',')


print "data"

print deliveryData


X = deliveryData[:, :-1]

Y = deliveryData[:, -1]


print "X:"

print X

print "Y: "

print Y


regr = linear_model.LinearRegression()


regr.fit(X, Y)


print "coefficients"

print regr.coef_

print "intercept: "

print regr.intercept_


xPred = [102, 6]

yPred = regr.predict(xPred)

print "predicted y: "

print yPred