机器学习：sklearn 中的年龄/净值回归，图像化展示效果

+++++++++++++++++++++++ 文件 studentMain.py  +++++++++++++++++++++++ start

#!/usr/bin/python

import numpy
import matplotlib
matplotlib.use('agg')


import matplotlib.pyplot as plt
from studentRegression import studentReg
from class_vis import prettyPicture, output_image


from ages_net_worths import ageNetWorthData


ages_train, ages_test, net_worths_train, net_worths_test = ageNetWorthData()






reg = studentReg(ages_train, net_worths_train)




plt.clf()
plt.scatter(ages_train, net_worths_train, color="b", label="train data")
plt.scatter(ages_test, net_worths_test, color="r", label="test data")
plt.plot(ages_test, reg.predict(ages_test), color="black")
plt.legend(loc=2)
plt.xlabel("ages")
plt.ylabel("net worths")




plt.savefig("test.png")

output_image("test.png", "png", open("test.png", "rb").read())

+++++++++++++++++++++++ 文件 studentMain.py  +++++++++++++++++++++++ end

+++++++++++++++++++++++ 文件 studentRegression.py  +++++++++++++++++++++++ start

from sklearn import linear_model


def studentReg(ages_train, net_worths_train):
    ### import the sklearn regression module, create, and train your regression
    ### name your regression reg
    
    ### your code goes here!
    reg = linear_model.LinearRegression()
    reg.fit(ages_train,net_worths_train)

    return reg

+++++++++++++++++++++++ 文件 studentRegression.py  +++++++++++++++++++++++ end