7.4多元线性回归实例1--python机器学习

原文地址
参考彭亮老师的视频教程：转载请注明出处及彭亮老师原创

视频教程： http://pan.baidu.com/s/1kVNe5EJ
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