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

1 vote67 views1 answer
Procfile for flask app
Python
2 votes100 views1 answer
Cos in python in degrees
Python
1 vote113 views1 answer
ModuleNotFoundError: No module named 'thread'
Python
9 votes69 views20 answers
Tkinter python
Python
1 vote117 views1 answer
Esp8266 micropython ds18b20
Python
291 votes1.1K views10 answers
Remove element from list python
Python
0 vote125 views1 answer
Django bootstrap
Python Django
0 vote141 views1 answer
Send message if user is banned discord.py
Python
1 vote102 views3 answers
Pip pyttsx3
Python
12 votes98 views4 answers
Unzip in python
Python