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
目的：求出b0,b1,...,bp
代码：
from numpy import genfromtxt
import numpy as np
from sklearn import datasets, linear_model
dataPath = r"E:\PycharmProjects\python\SimpleLinearRegretion\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)结果：data
[[100. 4. 9.3]
[ 50. 3. 4.8]
[100. 4. 8.9]
[100. 2. 6.5]
[ 50. 2. 4.2]
[ 80. 2. 6.2]
[ 75. 3. 7.4]
[ 65. 4. 6. ]
[ 90. 3. 7.6]
[ 90. 2. 6.1]]
X:
[[100. 4.]
[ 50. 3.]
[100. 4.]
[100. 2.]
[ 50. 2.]
[ 80. 2.]
[ 75. 3.]
[ 65. 4.]
[ 90. 3.]
[ 90. 2.]]
Y:
[9.3 4.8 8.9 6.5 4.2 6.2 7.4 6. 7.6 6.1]
coefficients
[0.0611346 0.92342537]
intercept:
-0.8687014667817126
predicted y:
[10.90757981]
代码：
from numpy import genfromtxt
import numpy as np
from sklearn import datasets, linear_model
dataPath = r"E:\PycharmProjects\python\SimpleLinearRegretion\DeliveryDummyDone.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)结果：
data
[[100. 4. 0. 1. 0. 9.3]
[ 50. 3. 1. 0. 0. 4.8]
[100. 4. 0. 1. 0. 8.9]
[100. 2. 0. 0. 1. 6.5]
[ 50. 2. 0. 0. 1. 4.2]
[ 80. 2. 0. 1. 0. 6.2]
[ 75. 3. 0. 1. 0. 7.4]
[ 65. 4. 1. 0. 0. 6. ]
[ 90. 3. 1. 0. 0. 7.6]]
X:
[[100. 4. 0. 1. 0.]
[ 50. 3. 1. 0. 0.]
[100. 4. 0. 1. 0.]
[100. 2. 0. 0. 1.]
[ 50. 2. 0. 0. 1.]
[ 80. 2. 0. 1. 0.]
[ 75. 3. 0. 1. 0.]
[ 65. 4. 1. 0. 0.]
[ 90. 3. 1. 0. 0.]]
Y:
[9.3 4.8 8.9 6.5 4.2 6.2 7.4 6. 7.6]
coefficients
[ 0.05553544 0.69257631 -0.17013278 0.57040007 -0.40026729]
intercept:
0.1999568891188117
进程已结束,退出代码0