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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=b 0 ＋b １ x 1 +b 2 x 2 + ... +b p x p 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