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#导入模块
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
from matplotlib.font_manager import FontProperties
#准备训练数据
X = [[147,9],[129,7],[141,9],[145,11],[142,11],[151,13]]
y = [[34],[23],[25],[47],[26],[46]]
#创建模型
model = LinearRegression()
#输入数据
model.fit(X,y)
#准备测试数据
X_test = [[149,11],[152,12],[140,8],[138,10],[132,7],[147,10]]
y_test = [[41],[37],[28],[27],[21],[38]]
#预测
predictions = model.predict(X_test)
#模型评估
print('R^2为%.2f'%model.score(X_test,y_test))
#输出数据
for i,prediction in enumerate(predictions):
print('Predicted:%s,Target:%s'%(prediction,y_test[i]))
#图形显示
font = FontProperties(fname=r'c:\Windows\Fonts\msyh.ttc',size=15)
plt.title('多元回归实际值与预测值',fontproperties=font)
plt.plot(y_test,label='y_test')
plt.plot(predictions,label='predictions')
plt.legend()
plt.show()