Scikit learn linear regression

from sklearn.linear_model import LinearRegression
X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
y = np.dot(X, np.array([1, 2])) + 3
reg = LinearRegression().fit(X, y)
reg.score(X, y)
reg.coef_
reg.intercept_
reg.predict(np.array([[3, 5]]))

Source: scikit-learn.org

Scikit learn linear regression

from sklearn.linear_model import LinearRegression
reg = LinearRegression()
reg.score(X, y) #Fit linear model
reg.coef_ #Estimated coefficients for the linear regression problem
reg.predict(y) #Predict using the linear model

Similar codes

4 votes271 views6 answers
Eval function in python
Python
37 votes189 views6 answers
List into string python
Python
6 votes145 views2 answers
Python calculate derivative of function
Python
0 vote110 views1 answer
Python read textfile
Python
0 vote140 views1 answer
NSDictionary fast access
Python
5 votes389 views1 answer
Rectangle in tkinter
Python
24 votes282 views1 answer
Python hour from date
Python
7 votes158 views1 answer
Python Emoji
Python
1 vote156 views1 answer
How to change help command on discord python
Python
-1 vote166 views2 answers
Httplib python
Python