sklearn线性拟合基本框架

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This is a simple example of LinearRegression

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Import libraries

import numpy as np
from sklearn.linear_model import LinearRegression
x=np.array([[1,1],[1,2],[2,2],[2,3]])

#y=1x_0+2x_1+3
y=np.dot(x,np.array([1,2]))+3

#Regression
reg=LinearRegression().fit(x,y)

#Returns the coefficient of determination R^2 of the prediction.
reg.score()

#one of values needed to regression ,here it is y
reg.coef_

#intercept
reg.intercept_

#Predict using the linear model,in other words,it is giving x values,predict the result.
#In this example,the coef equals something we do not known in the reality.
reg.predict(np.array([[3,5]]))